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You searched for subject:(machine learning AND constrained independent component analysis The methodology shown in this paper is unique). Showing records 1 – 30 of 44 total matches.

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Univerzitet u Beogradu

1. Savić, Aleksandar G. 1986-. Примена напредних статистичких метода у анализи сложених ЕПР и флуоресцентних спектара слободних радикала.

Degree: Fakultet za fizičku hemiju, 2016, Univerzitet u Beogradu

Физичка хемија / Physical Chemistry Хемометрија / Chemometrics

Спектри спин адуката спинског хватача DEPMPO омогућавају препознавање више типова слободних радикала. Са усложњавањем спектара, њихова анализа… (more)

Subjects/Keywords: Spin-trap DEPMPO allows recognition of several types of free radicals; thanks to the fact that each DEPMPO spin-adduct has characteristic EPR signal. As more complex spectra become; spectral analysis becomes more challenging task. Since the classical chemometrics methods successfully applied in spectra analysis do not provide desirable results; unique analytical procedure is proposed in this paper. This method is able to distinguish spectral mixtures built up to 6 free radical species; by applying blind source decomposition; machine learning and constrained independent component analysis. The methodology shown in this paper is unique; because it combines two types of spectroscopy; EPR spectroscopy and fluorescence spectroscopy. Such approach minimizes possible experimental errors originating from chemistry of fluorescence probes and spin-traps. Described statistical methods were modified for image analysis and tested on micrographs. It opens new field for research of free radical processes in living systems. Key words: Electron paramagnetic resonance (EPR); fluorescence spectroscopy; free radicals; multivariate analysis

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Savić, A. G. 1. (2016). Примена напредних статистичких метода у анализи сложених ЕПР и флуоресцентних спектара слободних радикала. (Thesis). Univerzitet u Beogradu. Retrieved from https://fedorabg.bg.ac.rs/fedora/get/o:10145/bdef:Content/get

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Savić, Aleksandar G 1986-. “Примена напредних статистичких метода у анализи сложених ЕПР и флуоресцентних спектара слободних радикала.” 2016. Thesis, Univerzitet u Beogradu. Accessed May 09, 2021. https://fedorabg.bg.ac.rs/fedora/get/o:10145/bdef:Content/get.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Savić, Aleksandar G 1986-. “Примена напредних статистичких метода у анализи сложених ЕПР и флуоресцентних спектара слободних радикала.” 2016. Web. 09 May 2021.

Vancouver:

Savić AG1. Примена напредних статистичких метода у анализи сложених ЕПР и флуоресцентних спектара слободних радикала. [Internet] [Thesis]. Univerzitet u Beogradu; 2016. [cited 2021 May 09]. Available from: https://fedorabg.bg.ac.rs/fedora/get/o:10145/bdef:Content/get.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Savić AG1. Примена напредних статистичких метода у анализи сложених ЕПР и флуоресцентних спектара слободних радикала. [Thesis]. Univerzitet u Beogradu; 2016. Available from: https://fedorabg.bg.ac.rs/fedora/get/o:10145/bdef:Content/get

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Oxford

2. Desmaison, Alban. Optimization for, and by, machine learning.

Degree: PhD, 2019, University of Oxford

 Optimization and machine learning are both extremely active research topics. In this thesis, we explore problems at the intersection of the two fields. In particular,… (more)

Subjects/Keywords: Machine learning; Constrained optimization

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APA (6th Edition):

Desmaison, A. (2019). Optimization for, and by, machine learning. (Doctoral Dissertation). University of Oxford. Retrieved from http://ora.ox.ac.uk/objects/uuid:7b9b387a-fcce-425c-8186-5d161789a52a ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.813610

Chicago Manual of Style (16th Edition):

Desmaison, Alban. “Optimization for, and by, machine learning.” 2019. Doctoral Dissertation, University of Oxford. Accessed May 09, 2021. http://ora.ox.ac.uk/objects/uuid:7b9b387a-fcce-425c-8186-5d161789a52a ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.813610.

MLA Handbook (7th Edition):

Desmaison, Alban. “Optimization for, and by, machine learning.” 2019. Web. 09 May 2021.

Vancouver:

Desmaison A. Optimization for, and by, machine learning. [Internet] [Doctoral dissertation]. University of Oxford; 2019. [cited 2021 May 09]. Available from: http://ora.ox.ac.uk/objects/uuid:7b9b387a-fcce-425c-8186-5d161789a52a ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.813610.

Council of Science Editors:

Desmaison A. Optimization for, and by, machine learning. [Doctoral Dissertation]. University of Oxford; 2019. Available from: http://ora.ox.ac.uk/objects/uuid:7b9b387a-fcce-425c-8186-5d161789a52a ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.813610

3. Tay, Noel Nuo Wi. Human-centric Semantic Reasoning and Optimization for Smart Home : スマートホームのための人間中心セマンティック推論と最適化.

Degree: 博士(工学), 2017, Tokyo Metropolitan University / 首都大学東京

首都大学東京, 2017-03-25, 博士(工学)

Subjects/Keywords: Smart home consists of various kinds of Internet of Tings (IoT) devices connected to the private house that cooperatively provide inhabitants (users) with proactive services related to comfort; security and safety. Examples of services include 1) manipulation of lighting and temperature based on time and context; 2) reminder service of user’s schedules by using the nearest output device; and 3) device organization to realize surveillance system. However; current smart homes are developed mostly from the viewpoint of technical capabilities; where users have to decide how the connected devices are going to serve them. They may have to setup the devices based on the available functionalities and specifications of the devices; and also have to alter their living styles according to the role of each device. Besides; most devices can only provide simple services independently. Œus; cooperation among the devices is important. On the other hand; human-centric approach; which centered on humans’ need to enhance their living experience; is an important technological paradigm where services are provided anywhere and anytime based on situation. Smart home abiding this approach should cooperatively maximize fulfillment of quality of life (QOL) for individual users subject to personal constraints. In this respect; the devices are bound to enable communication of information; and their operations are coordinated to deliver services cooperatively via a sequence of device actions called a plan. Due to personalization and automation; a number of problems have to be solved. First; a means of automatic binding between loosely coupled devices depending on services delivered have to be devised; as manual setup is impractical. Secondly; coordination of devices needs to generate complex plans; without requiring manual specification of sub-plans. Besides; issue of over-constrained goals during service provisions that arises from flawed or contradicting specification from multiple users should be considered. Apart from that; low training data in general environment setting for individual identification should be addressed. The aim of this research is to establish an integrated system for the human-centric smart home (HcSH) that provides personalized service through loosely coupled devices automatically. This research modularizes the overall system into three modules; which are human identification (HIM); automated planner (APM); and semantic reasoner (SRM). HIM helps select the appropriate QOL; SRM binds the devices by associating them with planning components; which are then used by APM to generate plans for device coordination to maximize QOL fulfillment. Chapter 1 gives the introduction and design motivation. Chapter 2 presents the related works and literature reviews; as well as justifications relevant to this thesis. Chapter 3 deals with HIM; which is realized via face identification. For face identification; problems faced are heavy computational load and insufficient learning data. The solution is to use transfer learning to handle data issue while being able to build generalized face model. For face model refinement; active learning is implemented. Experimental results show the method is competitive in terms of accuracy and computational cost compared to current state of the art. Chapter 4 presents APM; where planning via solving Constraint Satisfaction Problem (CSP) is laid out. CSP in planning is declarative without requiring prior specification of sub-plans; and can handle variables of larger domains. Due to the high possibility of having over-constrained QOL as in practical cases; CSP planner cannot fulfill all of them. An example is a contradicting TV channel request from 2 persons. Optimization through weighted CSP is therefore used to maximize QOL fulfillment. Experiments on weighted CSP shows that the method is capable of performing optimization while generating complex plans. Chapter 5 is on SRM; where knowledge representation is constructed by Web Ontology Language (OWL) description logic. It models knowledge on home and building layout and device functionalities. OWL is used because it is decidable and that it is endorsed by World Wide Web Consortium (W3C). We deal with case studies based on further inference on building state as an important example to discuss the applicability of the proposed method; and demonstrate the use of building ontology. This is followed by automated device binding and the method to generate basic planning components of rules in automated planning. Finally; an extension to robot complex planning is provided to demonstrate how it can be easily extended. Chapter 6 demonstrates the applicability of the HcSH; which integrates all three modules through its implementation in a prototype smart home with 5 rooms; which houses 2 persons. Various tests are performed to show the generated plans are near optimal without redundancy. Œe system is also shown to be scalable given increasing amount of devices. Case studies show that the system can perform well even under short time threshold. Finally; chapter 7 summarizes the thesis. Future vision of the work is also laid out; which is to implement it as a community-centric system.

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Tay, N. N. W. (2017). Human-centric Semantic Reasoning and Optimization for Smart Home : スマートホームのための人間中心セマンティック推論と最適化. (Thesis). Tokyo Metropolitan University / 首都大学東京. Retrieved from http://hdl.handle.net/10748/00009960

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Tay, Noel Nuo Wi. “Human-centric Semantic Reasoning and Optimization for Smart Home : スマートホームのための人間中心セマンティック推論と最適化.” 2017. Thesis, Tokyo Metropolitan University / 首都大学東京. Accessed May 09, 2021. http://hdl.handle.net/10748/00009960.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Tay, Noel Nuo Wi. “Human-centric Semantic Reasoning and Optimization for Smart Home : スマートホームのための人間中心セマンティック推論と最適化.” 2017. Web. 09 May 2021.

Vancouver:

Tay NNW. Human-centric Semantic Reasoning and Optimization for Smart Home : スマートホームのための人間中心セマンティック推論と最適化. [Internet] [Thesis]. Tokyo Metropolitan University / 首都大学東京; 2017. [cited 2021 May 09]. Available from: http://hdl.handle.net/10748/00009960.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Tay NNW. Human-centric Semantic Reasoning and Optimization for Smart Home : スマートホームのための人間中心セマンティック推論と最適化. [Thesis]. Tokyo Metropolitan University / 首都大学東京; 2017. Available from: http://hdl.handle.net/10748/00009960

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Manchester

4. Al-Garaawi, Nora Mohammed Sahib. MODELLING OF HUMAN AGEING, COMPOUND EMOTIONS, AND INTENSITY FOR AUTOMATIC FACIAL EXPRESSION RECOGNITION.

Degree: 2019, University of Manchester

 After decades of research, automatic facial expression recognition (AFER) has been shown to work well when restricted to subjects with a limited range of ages,… (more)

Subjects/Keywords: computer vision; machine learning; face representation; face descriptors; binary robust independent elementary features (BRIEF); facial features point detection; facial landmark localisation; random forest regression voting in a constrained local model framework (RFRV-CLM); compound emotions modelling; expression's Intensity modelling; age group estimation; apparent age; age effect on expression recognition

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APA (6th Edition):

Al-Garaawi, N. M. S. (2019). MODELLING OF HUMAN AGEING, COMPOUND EMOTIONS, AND INTENSITY FOR AUTOMATIC FACIAL EXPRESSION RECOGNITION. (Doctoral Dissertation). University of Manchester. Retrieved from http://www.manchester.ac.uk/escholar/uk-ac-man-scw:318504

Chicago Manual of Style (16th Edition):

Al-Garaawi, Nora Mohammed Sahib. “MODELLING OF HUMAN AGEING, COMPOUND EMOTIONS, AND INTENSITY FOR AUTOMATIC FACIAL EXPRESSION RECOGNITION.” 2019. Doctoral Dissertation, University of Manchester. Accessed May 09, 2021. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:318504.

MLA Handbook (7th Edition):

Al-Garaawi, Nora Mohammed Sahib. “MODELLING OF HUMAN AGEING, COMPOUND EMOTIONS, AND INTENSITY FOR AUTOMATIC FACIAL EXPRESSION RECOGNITION.” 2019. Web. 09 May 2021.

Vancouver:

Al-Garaawi NMS. MODELLING OF HUMAN AGEING, COMPOUND EMOTIONS, AND INTENSITY FOR AUTOMATIC FACIAL EXPRESSION RECOGNITION. [Internet] [Doctoral dissertation]. University of Manchester; 2019. [cited 2021 May 09]. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:318504.

Council of Science Editors:

Al-Garaawi NMS. MODELLING OF HUMAN AGEING, COMPOUND EMOTIONS, AND INTENSITY FOR AUTOMATIC FACIAL EXPRESSION RECOGNITION. [Doctoral Dissertation]. University of Manchester; 2019. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:318504


University of Illinois – Chicago

5. Haiyang He (448680). Constrained Surface Design for Projection Stereolithography.

Degree: 2019, University of Illinois – Chicago

 In Constrained Surface Projection Stereolithography (CSP-SL) processes, the separation of a newly cured layer from the constrained surface is a historical technical barrier and greatly… (more)

Subjects/Keywords: Uncategorized; Constrained Surface Projection Stereolithography; Radial microgroove; Air-diffusion channel; Textured constrained surface; Island constrained surface; Machine learning; Siamese Network

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APA (6th Edition):

(448680), H. H. (2019). Constrained Surface Design for Projection Stereolithography. (Thesis). University of Illinois – Chicago. Retrieved from http://hdl.handle.net/10.25417/uic.12480914.v1

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

(448680), Haiyang He. “Constrained Surface Design for Projection Stereolithography.” 2019. Thesis, University of Illinois – Chicago. Accessed May 09, 2021. http://hdl.handle.net/10.25417/uic.12480914.v1.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

(448680), Haiyang He. “Constrained Surface Design for Projection Stereolithography.” 2019. Web. 09 May 2021.

Vancouver:

(448680) HH. Constrained Surface Design for Projection Stereolithography. [Internet] [Thesis]. University of Illinois – Chicago; 2019. [cited 2021 May 09]. Available from: http://hdl.handle.net/10.25417/uic.12480914.v1.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

(448680) HH. Constrained Surface Design for Projection Stereolithography. [Thesis]. University of Illinois – Chicago; 2019. Available from: http://hdl.handle.net/10.25417/uic.12480914.v1

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Minnesota

6. Ambalakkat, Sarath Mohan. Optimization of Constrained Random Verification using Machine Learning.

Degree: M.S.E.E., Electrical Engineering, 2018, University of Minnesota

Constrained random simulations play a critical role in Design Verification today. But the effort and time spent to manually update the input constraints, analyzing and… (more)

Subjects/Keywords: ANN; Constrained Random Verification; Design Verification; Machine Learning; Neural Networks; UVM

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APA (6th Edition):

Ambalakkat, S. M. (2018). Optimization of Constrained Random Verification using Machine Learning. (Masters Thesis). University of Minnesota. Retrieved from http://hdl.handle.net/11299/198982

Chicago Manual of Style (16th Edition):

Ambalakkat, Sarath Mohan. “Optimization of Constrained Random Verification using Machine Learning.” 2018. Masters Thesis, University of Minnesota. Accessed May 09, 2021. http://hdl.handle.net/11299/198982.

MLA Handbook (7th Edition):

Ambalakkat, Sarath Mohan. “Optimization of Constrained Random Verification using Machine Learning.” 2018. Web. 09 May 2021.

Vancouver:

Ambalakkat SM. Optimization of Constrained Random Verification using Machine Learning. [Internet] [Masters thesis]. University of Minnesota; 2018. [cited 2021 May 09]. Available from: http://hdl.handle.net/11299/198982.

Council of Science Editors:

Ambalakkat SM. Optimization of Constrained Random Verification using Machine Learning. [Masters Thesis]. University of Minnesota; 2018. Available from: http://hdl.handle.net/11299/198982


University of Toronto

7. Mahmood, Rafid. Learning to Solve Optimization Problems with Hidden Components: Applications in Automated Treatment Planning.

Degree: PhD, 2020, University of Toronto

 Designing optimization models that capture decision-maker preferences typically requires guidance from domain experts. We can instead employ machine learning (ML) to design contextual optimization models… (more)

Subjects/Keywords: constrained optimization; machine learning; medical decision-making; radiation therapy; 0796

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APA (6th Edition):

Mahmood, R. (2020). Learning to Solve Optimization Problems with Hidden Components: Applications in Automated Treatment Planning. (Doctoral Dissertation). University of Toronto. Retrieved from http://hdl.handle.net/1807/103339

Chicago Manual of Style (16th Edition):

Mahmood, Rafid. “Learning to Solve Optimization Problems with Hidden Components: Applications in Automated Treatment Planning.” 2020. Doctoral Dissertation, University of Toronto. Accessed May 09, 2021. http://hdl.handle.net/1807/103339.

MLA Handbook (7th Edition):

Mahmood, Rafid. “Learning to Solve Optimization Problems with Hidden Components: Applications in Automated Treatment Planning.” 2020. Web. 09 May 2021.

Vancouver:

Mahmood R. Learning to Solve Optimization Problems with Hidden Components: Applications in Automated Treatment Planning. [Internet] [Doctoral dissertation]. University of Toronto; 2020. [cited 2021 May 09]. Available from: http://hdl.handle.net/1807/103339.

Council of Science Editors:

Mahmood R. Learning to Solve Optimization Problems with Hidden Components: Applications in Automated Treatment Planning. [Doctoral Dissertation]. University of Toronto; 2020. Available from: http://hdl.handle.net/1807/103339


Georgia Tech

8. Mao, Yi. Domain knowledge, uncertainty, and parameter constraints.

Degree: PhD, Computing, 2010, Georgia Tech

Subjects/Keywords: Sentiment analysis; Constrained optimization; Empirical bayes; Supervised learning; Supervised learning (Machine learning); Machine learning; Artificial intelligence

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APA (6th Edition):

Mao, Y. (2010). Domain knowledge, uncertainty, and parameter constraints. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/37295

Chicago Manual of Style (16th Edition):

Mao, Yi. “Domain knowledge, uncertainty, and parameter constraints.” 2010. Doctoral Dissertation, Georgia Tech. Accessed May 09, 2021. http://hdl.handle.net/1853/37295.

MLA Handbook (7th Edition):

Mao, Yi. “Domain knowledge, uncertainty, and parameter constraints.” 2010. Web. 09 May 2021.

Vancouver:

Mao Y. Domain knowledge, uncertainty, and parameter constraints. [Internet] [Doctoral dissertation]. Georgia Tech; 2010. [cited 2021 May 09]. Available from: http://hdl.handle.net/1853/37295.

Council of Science Editors:

Mao Y. Domain knowledge, uncertainty, and parameter constraints. [Doctoral Dissertation]. Georgia Tech; 2010. Available from: http://hdl.handle.net/1853/37295


University of South Florida

9. Laguduva Ramnath, Vishalini. Machine Learning for the Internet of Things: Applications, Implementation, and Security.

Degree: 2020, University of South Florida

 Artificial intelligence and ubiquitous sensor systems have seen tremendous advances in recent times, resulting in groundbreaking impact across domains such as healthcare, entertainment, and transportation… (more)

Subjects/Keywords: Constrained Platforms; Hardware Security; Internet of Medical Things; Machine Learning; Computer Engineering; Computer Sciences

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APA (6th Edition):

Laguduva Ramnath, V. (2020). Machine Learning for the Internet of Things: Applications, Implementation, and Security. (Thesis). University of South Florida. Retrieved from https://scholarcommons.usf.edu/etd/8240

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Laguduva Ramnath, Vishalini. “Machine Learning for the Internet of Things: Applications, Implementation, and Security.” 2020. Thesis, University of South Florida. Accessed May 09, 2021. https://scholarcommons.usf.edu/etd/8240.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Laguduva Ramnath, Vishalini. “Machine Learning for the Internet of Things: Applications, Implementation, and Security.” 2020. Web. 09 May 2021.

Vancouver:

Laguduva Ramnath V. Machine Learning for the Internet of Things: Applications, Implementation, and Security. [Internet] [Thesis]. University of South Florida; 2020. [cited 2021 May 09]. Available from: https://scholarcommons.usf.edu/etd/8240.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Laguduva Ramnath V. Machine Learning for the Internet of Things: Applications, Implementation, and Security. [Thesis]. University of South Florida; 2020. Available from: https://scholarcommons.usf.edu/etd/8240

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Illinois – Urbana-Champaign

10. Pasternack, Jeffrey. Knowing Who to Trust and What to Believe in the Presence of Conflicting Information.

Degree: PhD, 0112, 2012, University of Illinois – Urbana-Champaign

 The Information Age has created an increasing abundance of data and has, thanks to the rise of the Internet, made that knowledge instantly available to… (more)

Subjects/Keywords: trust; trustworthiness; information trustworthiness; information trust; comprehensive trust metrics; subjective truth; fact-finders; fact-finding; factfinders; factfinding; generalized fact-finding; generalized fact-finders; constrained fact-finding; constrained fact-finders; Generalized Constrained Models (GCMs); latent trust analysis; latent trustworthiness analysis; Latent Trust Analysis (LTA); belief; information filtering; structured learning; constrained structured learning; constrained learning

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Pasternack, J. (2012). Knowing Who to Trust and What to Believe in the Presence of Conflicting Information. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/29516

Chicago Manual of Style (16th Edition):

Pasternack, Jeffrey. “Knowing Who to Trust and What to Believe in the Presence of Conflicting Information.” 2012. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed May 09, 2021. http://hdl.handle.net/2142/29516.

MLA Handbook (7th Edition):

Pasternack, Jeffrey. “Knowing Who to Trust and What to Believe in the Presence of Conflicting Information.” 2012. Web. 09 May 2021.

Vancouver:

Pasternack J. Knowing Who to Trust and What to Believe in the Presence of Conflicting Information. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2012. [cited 2021 May 09]. Available from: http://hdl.handle.net/2142/29516.

Council of Science Editors:

Pasternack J. Knowing Who to Trust and What to Believe in the Presence of Conflicting Information. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2012. Available from: http://hdl.handle.net/2142/29516


Delft University of Technology

11. Verburg, Floris (author). Improving RCPSP algorithms using machine learning methods.

Degree: 2018, Delft University of Technology

 For performing technical maintenance, it is important to keep a detailed schedule of resources and temporal constraints. The Resource Constrained Project Scheduling Problem (RCPSP) is(more)

Subjects/Keywords: Scheduling; Maintenance scheduling; Resource Constrained Project Scheduling Problem; Precedence Constraint Posting; Machine learning; Monte Carlo simulation

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APA (6th Edition):

Verburg, F. (. (2018). Improving RCPSP algorithms using machine learning methods. (Masters Thesis). Delft University of Technology. Retrieved from http://resolver.tudelft.nl/uuid:82c2c44b-c3d6-4d9a-9b2f-49a0f71eb1a3

Chicago Manual of Style (16th Edition):

Verburg, Floris (author). “Improving RCPSP algorithms using machine learning methods.” 2018. Masters Thesis, Delft University of Technology. Accessed May 09, 2021. http://resolver.tudelft.nl/uuid:82c2c44b-c3d6-4d9a-9b2f-49a0f71eb1a3.

MLA Handbook (7th Edition):

Verburg, Floris (author). “Improving RCPSP algorithms using machine learning methods.” 2018. Web. 09 May 2021.

Vancouver:

Verburg F(. Improving RCPSP algorithms using machine learning methods. [Internet] [Masters thesis]. Delft University of Technology; 2018. [cited 2021 May 09]. Available from: http://resolver.tudelft.nl/uuid:82c2c44b-c3d6-4d9a-9b2f-49a0f71eb1a3.

Council of Science Editors:

Verburg F(. Improving RCPSP algorithms using machine learning methods. [Masters Thesis]. Delft University of Technology; 2018. Available from: http://resolver.tudelft.nl/uuid:82c2c44b-c3d6-4d9a-9b2f-49a0f71eb1a3


University of Florida

12. Kriminger, Evan G. An Effective and Robust Method for Active Constrained Clustering.

Degree: PhD, Electrical and Computer Engineering, 2015, University of Florida

Constrained clustering methods seek to partition a dataset in accordance with the distance properties of the data, while also adhering to a set of linkage… (more)

Subjects/Keywords: Active learning; Datasets; Distance functions; Error rates; International conferences; Machine learning; Oracles; Outliers; Sonar; Voting; active-learning  – clustering  – constrained-clustering  – semi-supervised-learning

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Kriminger, E. G. (2015). An Effective and Robust Method for Active Constrained Clustering. (Doctoral Dissertation). University of Florida. Retrieved from https://ufdc.ufl.edu/UFE0049468

Chicago Manual of Style (16th Edition):

Kriminger, Evan G. “An Effective and Robust Method for Active Constrained Clustering.” 2015. Doctoral Dissertation, University of Florida. Accessed May 09, 2021. https://ufdc.ufl.edu/UFE0049468.

MLA Handbook (7th Edition):

Kriminger, Evan G. “An Effective and Robust Method for Active Constrained Clustering.” 2015. Web. 09 May 2021.

Vancouver:

Kriminger EG. An Effective and Robust Method for Active Constrained Clustering. [Internet] [Doctoral dissertation]. University of Florida; 2015. [cited 2021 May 09]. Available from: https://ufdc.ufl.edu/UFE0049468.

Council of Science Editors:

Kriminger EG. An Effective and Robust Method for Active Constrained Clustering. [Doctoral Dissertation]. University of Florida; 2015. Available from: https://ufdc.ufl.edu/UFE0049468

13. Al-Garaawi, Nora. Modelling of human ageing, compound emotions, and intensity for automatic facial expression recognition.

Degree: PhD, 2019, University of Manchester

 After decades of research, automatic facial expression recognition (AFER) has been shown to work well when restricted to subjects with a limited range of ages,… (more)

Subjects/Keywords: 004; compound emotions modelling; age effect on expression recognition; apparent age; age group estimation; expression's Intensity modelling; random forest regression voting in a constrained local model framework (RFRV-CLM); machine learning; facial features point detection; facial landmark localisation; face representation; computer vision; binary robust independent elementary features (BRIEF); face descriptors

…that the AU does not appear in either of the two subordinate categories. This table is… …crucial area of research in the fields of computer science and machine learning. AFER, which… …between the emotion features and the neutral features can be seen in right column. This figure… …Constrained Local Model (CLM) search algorithm. This figure is adapted from (Saragih… …Visualization of ageing details removal from the face image. This figure is adapted from Guo et al… 

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Al-Garaawi, N. (2019). Modelling of human ageing, compound emotions, and intensity for automatic facial expression recognition. (Doctoral Dissertation). University of Manchester. Retrieved from https://www.research.manchester.ac.uk/portal/en/theses/modelling-of-human-ageing-compound-emotions-and-intensity-for-automatic-facial-expression-recognition(e798eb3c-d323-4d75-90e7-181683ba243f).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.771497

Chicago Manual of Style (16th Edition):

Al-Garaawi, Nora. “Modelling of human ageing, compound emotions, and intensity for automatic facial expression recognition.” 2019. Doctoral Dissertation, University of Manchester. Accessed May 09, 2021. https://www.research.manchester.ac.uk/portal/en/theses/modelling-of-human-ageing-compound-emotions-and-intensity-for-automatic-facial-expression-recognition(e798eb3c-d323-4d75-90e7-181683ba243f).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.771497.

MLA Handbook (7th Edition):

Al-Garaawi, Nora. “Modelling of human ageing, compound emotions, and intensity for automatic facial expression recognition.” 2019. Web. 09 May 2021.

Vancouver:

Al-Garaawi N. Modelling of human ageing, compound emotions, and intensity for automatic facial expression recognition. [Internet] [Doctoral dissertation]. University of Manchester; 2019. [cited 2021 May 09]. Available from: https://www.research.manchester.ac.uk/portal/en/theses/modelling-of-human-ageing-compound-emotions-and-intensity-for-automatic-facial-expression-recognition(e798eb3c-d323-4d75-90e7-181683ba243f).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.771497.

Council of Science Editors:

Al-Garaawi N. Modelling of human ageing, compound emotions, and intensity for automatic facial expression recognition. [Doctoral Dissertation]. University of Manchester; 2019. Available from: https://www.research.manchester.ac.uk/portal/en/theses/modelling-of-human-ageing-compound-emotions-and-intensity-for-automatic-facial-expression-recognition(e798eb3c-d323-4d75-90e7-181683ba243f).html ; https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.771497


Wright State University

14. Goodman, Garrett G. Design of a Novel Wearable Ultrasound Vest for Autonomous Monitoring of the Heart Using Machine Learning.

Degree: PhD, Computer Science and Engineering PhD, 2020, Wright State University

 As the population of older individuals increases worldwide, the number of people with cardiovascular issues and diseases is also increasing. The rate at which individuals… (more)

Subjects/Keywords: Computer Science; Biomedical Engineering; Biomedical Research; Medical Imaging; medical imaging; ultrasound; ultrasonography; ultrasound transducers; computer vision; heart; cardiovascular; stereo vision; neural networks; modeling; machine learning; extreme learning machine; constrained state-preserved extreme learning machine

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Goodman, G. G. (2020). Design of a Novel Wearable Ultrasound Vest for Autonomous Monitoring of the Heart Using Machine Learning. (Doctoral Dissertation). Wright State University. Retrieved from http://rave.ohiolink.edu/etdc/view?acc_num=wright1607605597491118

Chicago Manual of Style (16th Edition):

Goodman, Garrett G. “Design of a Novel Wearable Ultrasound Vest for Autonomous Monitoring of the Heart Using Machine Learning.” 2020. Doctoral Dissertation, Wright State University. Accessed May 09, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=wright1607605597491118.

MLA Handbook (7th Edition):

Goodman, Garrett G. “Design of a Novel Wearable Ultrasound Vest for Autonomous Monitoring of the Heart Using Machine Learning.” 2020. Web. 09 May 2021.

Vancouver:

Goodman GG. Design of a Novel Wearable Ultrasound Vest for Autonomous Monitoring of the Heart Using Machine Learning. [Internet] [Doctoral dissertation]. Wright State University; 2020. [cited 2021 May 09]. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1607605597491118.

Council of Science Editors:

Goodman GG. Design of a Novel Wearable Ultrasound Vest for Autonomous Monitoring of the Heart Using Machine Learning. [Doctoral Dissertation]. Wright State University; 2020. Available from: http://rave.ohiolink.edu/etdc/view?acc_num=wright1607605597491118


University of Florida

15. Dobbins, Peter J. Scene Analysis Using the Markov Ground Region Segmentation System (MGRSS).

Degree: PhD, Computer Engineering - Computer and Information Science and Engineering, 2017, University of Florida

This work performs scene analysis, representing and understanding the elements contained in a defined area under the ground. Elements of interest include: the ground layer,… (more)

Subjects/Keywords: constrained-clustering  – ground-penetrating-radar  – image-segmentation  – markov-random-field  – scene-analysis  – semi-supervised-clustering  – semi-supervised-learning

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Dobbins, P. J. (2017). Scene Analysis Using the Markov Ground Region Segmentation System (MGRSS). (Doctoral Dissertation). University of Florida. Retrieved from https://ufdc.ufl.edu/UFE0051788

Chicago Manual of Style (16th Edition):

Dobbins, Peter J. “Scene Analysis Using the Markov Ground Region Segmentation System (MGRSS).” 2017. Doctoral Dissertation, University of Florida. Accessed May 09, 2021. https://ufdc.ufl.edu/UFE0051788.

MLA Handbook (7th Edition):

Dobbins, Peter J. “Scene Analysis Using the Markov Ground Region Segmentation System (MGRSS).” 2017. Web. 09 May 2021.

Vancouver:

Dobbins PJ. Scene Analysis Using the Markov Ground Region Segmentation System (MGRSS). [Internet] [Doctoral dissertation]. University of Florida; 2017. [cited 2021 May 09]. Available from: https://ufdc.ufl.edu/UFE0051788.

Council of Science Editors:

Dobbins PJ. Scene Analysis Using the Markov Ground Region Segmentation System (MGRSS). [Doctoral Dissertation]. University of Florida; 2017. Available from: https://ufdc.ufl.edu/UFE0051788


University of Newcastle

16. Houliston, Trent James. Software architecture and computer vision for resource constrained robotics.

Degree: PhD, 2018, University of Newcastle

Research Doctorate - Doctor of Philosophy (PhD)

This thesis identifies the restrictions that resource-constrained robotic platforms experience in relation to their software architecture and computer… (more)

Subjects/Keywords: software architecture; machine learning; RoboCup; latency; real-time; vision graph; co-messaging; domain specific language; computer vision; visual mesh; message passing; convolutional neural network; blackboard; robotics; resource constrained; lookup table

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Houliston, T. J. (2018). Software architecture and computer vision for resource constrained robotics. (Doctoral Dissertation). University of Newcastle. Retrieved from http://hdl.handle.net/1959.13/1389336

Chicago Manual of Style (16th Edition):

Houliston, Trent James. “Software architecture and computer vision for resource constrained robotics.” 2018. Doctoral Dissertation, University of Newcastle. Accessed May 09, 2021. http://hdl.handle.net/1959.13/1389336.

MLA Handbook (7th Edition):

Houliston, Trent James. “Software architecture and computer vision for resource constrained robotics.” 2018. Web. 09 May 2021.

Vancouver:

Houliston TJ. Software architecture and computer vision for resource constrained robotics. [Internet] [Doctoral dissertation]. University of Newcastle; 2018. [cited 2021 May 09]. Available from: http://hdl.handle.net/1959.13/1389336.

Council of Science Editors:

Houliston TJ. Software architecture and computer vision for resource constrained robotics. [Doctoral Dissertation]. University of Newcastle; 2018. Available from: http://hdl.handle.net/1959.13/1389336

17. Do, Quang. Background knowledge in learning-based relation extraction.

Degree: PhD, 0112, 2012, University of Illinois – Urbana-Champaign

 In this thesis, we study the importance of background knowledge in relation extraction systems. We not only demonstrate the benefits of leveraging background knowledge to… (more)

Subjects/Keywords: background knowledge; relation extraction; machine learning; constrained conditional model; inference

…Apple Inc. is a sibling of the term Microsoft. In our work, we use a machine learning approach… …coreference is also shown to be very beneficial in biasing the final outputs of the system. Next, we… …more detailed review on the related work of this research direction is presented in Chapter 5… …same as other linear models in learning. Furthermore, it is possible to set the value of… …approach in Section 3.2. The learning component and the inference model of our approach are… 

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Do, Q. (2012). Background knowledge in learning-based relation extraction. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/34379

Chicago Manual of Style (16th Edition):

Do, Quang. “Background knowledge in learning-based relation extraction.” 2012. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed May 09, 2021. http://hdl.handle.net/2142/34379.

MLA Handbook (7th Edition):

Do, Quang. “Background knowledge in learning-based relation extraction.” 2012. Web. 09 May 2021.

Vancouver:

Do Q. Background knowledge in learning-based relation extraction. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2012. [cited 2021 May 09]. Available from: http://hdl.handle.net/2142/34379.

Council of Science Editors:

Do Q. Background knowledge in learning-based relation extraction. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2012. Available from: http://hdl.handle.net/2142/34379

18. Zhou, Zhiqiang. Theory and applications of first-order methods for convex optimization with function constraints.

Degree: PhD, Industrial and Systems Engineering, 2020, Georgia Tech

This dissertation focuses on the development of efficient first-order methods for function constrained convex optimization and their applications in a few different areas, including healthcare,… (more)

Subjects/Keywords: First-order methods; Function constrained optimization; Machine learning

…CSPA. The remaining part of this paper is organized as follows. In Section 2, we present the… …finance and machine learning. The thesis consists of three major studies. The first part of the… …of our knowledge, this is the first time that such optimal SA methods for solving… …functional or expectation constrained stochastic optimization are presented in the literature. In… …classification and metric learning problem, respectively. The second part of the thesis is devoted to… 

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APA (6th Edition):

Zhou, Z. (2020). Theory and applications of first-order methods for convex optimization with function constraints. (Doctoral Dissertation). Georgia Tech. Retrieved from http://hdl.handle.net/1853/63664

Chicago Manual of Style (16th Edition):

Zhou, Zhiqiang. “Theory and applications of first-order methods for convex optimization with function constraints.” 2020. Doctoral Dissertation, Georgia Tech. Accessed May 09, 2021. http://hdl.handle.net/1853/63664.

MLA Handbook (7th Edition):

Zhou, Zhiqiang. “Theory and applications of first-order methods for convex optimization with function constraints.” 2020. Web. 09 May 2021.

Vancouver:

Zhou Z. Theory and applications of first-order methods for convex optimization with function constraints. [Internet] [Doctoral dissertation]. Georgia Tech; 2020. [cited 2021 May 09]. Available from: http://hdl.handle.net/1853/63664.

Council of Science Editors:

Zhou Z. Theory and applications of first-order methods for convex optimization with function constraints. [Doctoral Dissertation]. Georgia Tech; 2020. Available from: http://hdl.handle.net/1853/63664

19. Rizzolo, Nicholas. Learning based programming.

Degree: PhD, 0112, 2012, University of Illinois – Urbana-Champaign

Machine learning (ML) is the study of representations and algorithms used for building functions that improve their behavior with experience. Today, researchers in many domains… (more)

Subjects/Keywords: Learning Based Programming; Learning Based Java; constrained conditional model; machine learning

…Language Processing ix Chapter 1 Introduction Machine learning (ML) is the study… …so is a prerequisite for algorithm independent composability. To address this question, in… …approaches are summarized in Table 2.1. As shown in the table, there is limited support for model… …model’s structure is then evaluated after learning with the parameters filled in. Thus, PRISM is… …However, learning has not been incorporated in the language, and inference is approximate and… 

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APA (6th Edition):

Rizzolo, N. (2012). Learning based programming. (Doctoral Dissertation). University of Illinois – Urbana-Champaign. Retrieved from http://hdl.handle.net/2142/29738

Chicago Manual of Style (16th Edition):

Rizzolo, Nicholas. “Learning based programming.” 2012. Doctoral Dissertation, University of Illinois – Urbana-Champaign. Accessed May 09, 2021. http://hdl.handle.net/2142/29738.

MLA Handbook (7th Edition):

Rizzolo, Nicholas. “Learning based programming.” 2012. Web. 09 May 2021.

Vancouver:

Rizzolo N. Learning based programming. [Internet] [Doctoral dissertation]. University of Illinois – Urbana-Champaign; 2012. [cited 2021 May 09]. Available from: http://hdl.handle.net/2142/29738.

Council of Science Editors:

Rizzolo N. Learning based programming. [Doctoral Dissertation]. University of Illinois – Urbana-Champaign; 2012. Available from: http://hdl.handle.net/2142/29738

20. Pouilly-Cathelain, Maxime. Synthèse de correcteurs s’adaptant à des critères multiples de haut niveau par la commande prédictive et les réseaux de neurones : Synthesis of controllers adapting to multiple high-level criteria by model predictive control and neural networks.

Degree: Docteur es, Automatique, 2020, université Paris-Saclay

Cette thèse porte sur la commande des systèmes non linéaires soumis à des contraintes non différentiables ou non convexes. L'objectif est de pouvoir réaliser une… (more)

Subjects/Keywords: Commande prédictive non linéaire; Commande sous contraintes; Contraintes non différentiables; Fonctions barrières; Ensembles invariants; Optimisation sans gradient; Stabilité; Robustesse; Réseaux de neurones; Apprentissage; Nonlinear Model Predictive Control; Constrained control; Nondifferentiable Constraints; Barrier functions; Invariant sets; Gradient-free optimization; Stability; Robustness; Neural networks; Machine Learning

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APA (6th Edition):

Pouilly-Cathelain, M. (2020). Synthèse de correcteurs s’adaptant à des critères multiples de haut niveau par la commande prédictive et les réseaux de neurones : Synthesis of controllers adapting to multiple high-level criteria by model predictive control and neural networks. (Doctoral Dissertation). université Paris-Saclay. Retrieved from http://www.theses.fr/2020UPASG019

Chicago Manual of Style (16th Edition):

Pouilly-Cathelain, Maxime. “Synthèse de correcteurs s’adaptant à des critères multiples de haut niveau par la commande prédictive et les réseaux de neurones : Synthesis of controllers adapting to multiple high-level criteria by model predictive control and neural networks.” 2020. Doctoral Dissertation, université Paris-Saclay. Accessed May 09, 2021. http://www.theses.fr/2020UPASG019.

MLA Handbook (7th Edition):

Pouilly-Cathelain, Maxime. “Synthèse de correcteurs s’adaptant à des critères multiples de haut niveau par la commande prédictive et les réseaux de neurones : Synthesis of controllers adapting to multiple high-level criteria by model predictive control and neural networks.” 2020. Web. 09 May 2021.

Vancouver:

Pouilly-Cathelain M. Synthèse de correcteurs s’adaptant à des critères multiples de haut niveau par la commande prédictive et les réseaux de neurones : Synthesis of controllers adapting to multiple high-level criteria by model predictive control and neural networks. [Internet] [Doctoral dissertation]. université Paris-Saclay; 2020. [cited 2021 May 09]. Available from: http://www.theses.fr/2020UPASG019.

Council of Science Editors:

Pouilly-Cathelain M. Synthèse de correcteurs s’adaptant à des critères multiples de haut niveau par la commande prédictive et les réseaux de neurones : Synthesis of controllers adapting to multiple high-level criteria by model predictive control and neural networks. [Doctoral Dissertation]. université Paris-Saclay; 2020. Available from: http://www.theses.fr/2020UPASG019

21. ZHOU PAN. STRUCTURED DATA ANALYSIS: MODELS, ALGORITHMS AND THEORIES.

Degree: 2019, National University of Singapore

Subjects/Keywords: structured data analysis; low-rank tensor analysis; constrained optimization; Riemannian optimization; deep learning theory; generalization theory

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

PAN, Z. (2019). STRUCTURED DATA ANALYSIS: MODELS, ALGORITHMS AND THEORIES. (Thesis). National University of Singapore. Retrieved from https://scholarbank.nus.edu.sg/handle/10635/167559

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

PAN, ZHOU. “STRUCTURED DATA ANALYSIS: MODELS, ALGORITHMS AND THEORIES.” 2019. Thesis, National University of Singapore. Accessed May 09, 2021. https://scholarbank.nus.edu.sg/handle/10635/167559.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

PAN, ZHOU. “STRUCTURED DATA ANALYSIS: MODELS, ALGORITHMS AND THEORIES.” 2019. Web. 09 May 2021.

Vancouver:

PAN Z. STRUCTURED DATA ANALYSIS: MODELS, ALGORITHMS AND THEORIES. [Internet] [Thesis]. National University of Singapore; 2019. [cited 2021 May 09]. Available from: https://scholarbank.nus.edu.sg/handle/10635/167559.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

PAN Z. STRUCTURED DATA ANALYSIS: MODELS, ALGORITHMS AND THEORIES. [Thesis]. National University of Singapore; 2019. Available from: https://scholarbank.nus.edu.sg/handle/10635/167559

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


Indian Institute of Science

22. Jagarlapudi, Saketha Nath. Learning Algorithms Using Chance-Constrained Programs.

Degree: PhD, Faculty of Engineering, 2010, Indian Institute of Science

This thesis explores Chance-Constrained Programming (CCP) in the context of learning. It is shown that chance-constraint approaches lead to improved algorithms for three important learning(more)

Subjects/Keywords: Machine Learning; Classification; Dataset Classification; Ordinal Regression (OR); Chance-Constrained Programming (CCP); Classification - Algorithms; Ordinal Regression - Algorithms; Machine Learning - Algorithms; Second Order Cone Programs (SOCPs); Maximum Margin Classification; Focused Crawling; Large Datasets; Error Rates; Computer Science

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APA (6th Edition):

Jagarlapudi, S. N. (2010). Learning Algorithms Using Chance-Constrained Programs. (Doctoral Dissertation). Indian Institute of Science. Retrieved from http://etd.iisc.ac.in/handle/2005/733

Chicago Manual of Style (16th Edition):

Jagarlapudi, Saketha Nath. “Learning Algorithms Using Chance-Constrained Programs.” 2010. Doctoral Dissertation, Indian Institute of Science. Accessed May 09, 2021. http://etd.iisc.ac.in/handle/2005/733.

MLA Handbook (7th Edition):

Jagarlapudi, Saketha Nath. “Learning Algorithms Using Chance-Constrained Programs.” 2010. Web. 09 May 2021.

Vancouver:

Jagarlapudi SN. Learning Algorithms Using Chance-Constrained Programs. [Internet] [Doctoral dissertation]. Indian Institute of Science; 2010. [cited 2021 May 09]. Available from: http://etd.iisc.ac.in/handle/2005/733.

Council of Science Editors:

Jagarlapudi SN. Learning Algorithms Using Chance-Constrained Programs. [Doctoral Dissertation]. Indian Institute of Science; 2010. Available from: http://etd.iisc.ac.in/handle/2005/733


Monash University

23. Salerno, Christopher. Developing a Mobile Digital Badge System for a Resource Constrained Environment.

Degree: Information Technology, 2017, Monash University

 South Africa’s educational system is currently facing certain challenges that prevent learners from fully engaging in classes, which is particularly evident within rural areas. In… (more)

Subjects/Keywords: Uncategorized; HCI4D; Resource constrained environments; Digital badges; Human centered computing; Mobile learning; Teacher professional development

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APA (6th Edition):

Salerno, C. (2017). Developing a Mobile Digital Badge System for a Resource Constrained Environment. (Thesis). Monash University. Retrieved from http://hdl.handle.net/10.4225/03/58ae1d2b9ea67

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Salerno, Christopher. “Developing a Mobile Digital Badge System for a Resource Constrained Environment.” 2017. Thesis, Monash University. Accessed May 09, 2021. http://hdl.handle.net/10.4225/03/58ae1d2b9ea67.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Salerno, Christopher. “Developing a Mobile Digital Badge System for a Resource Constrained Environment.” 2017. Web. 09 May 2021.

Vancouver:

Salerno C. Developing a Mobile Digital Badge System for a Resource Constrained Environment. [Internet] [Thesis]. Monash University; 2017. [cited 2021 May 09]. Available from: http://hdl.handle.net/10.4225/03/58ae1d2b9ea67.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Salerno C. Developing a Mobile Digital Badge System for a Resource Constrained Environment. [Thesis]. Monash University; 2017. Available from: http://hdl.handle.net/10.4225/03/58ae1d2b9ea67

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Southern California

24. Lee, Hyokyeong. Parameter estimation to infer injector-producer relationships in oil fields: from hybrid constrained nonlinear optimization to inference in probabilistic graphical model.

Degree: PhD, Computer Science, 2010, University of Southern California

 In petroleum community, the oil field optimization, i.e., minimizing the operational cost and maximizing the oil recovery, is a challenging problem. One of the popular… (more)

Subjects/Keywords: hybrid optimization; constrained nonlinear optimization; constrained linear least squares; dimensionality reduction; sequential quadratic programming; quasi-Newton method; line search; injector-producer relationship; capacitance-resistive model; structure learning of factor graphs; locality principle; belief discrepancies; large-scale constrained nonlinear optimization; factor graph and the sum-product algorithm

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APA (6th Edition):

Lee, H. (2010). Parameter estimation to infer injector-producer relationships in oil fields: from hybrid constrained nonlinear optimization to inference in probabilistic graphical model. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/367302/rec/4917

Chicago Manual of Style (16th Edition):

Lee, Hyokyeong. “Parameter estimation to infer injector-producer relationships in oil fields: from hybrid constrained nonlinear optimization to inference in probabilistic graphical model.” 2010. Doctoral Dissertation, University of Southern California. Accessed May 09, 2021. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/367302/rec/4917.

MLA Handbook (7th Edition):

Lee, Hyokyeong. “Parameter estimation to infer injector-producer relationships in oil fields: from hybrid constrained nonlinear optimization to inference in probabilistic graphical model.” 2010. Web. 09 May 2021.

Vancouver:

Lee H. Parameter estimation to infer injector-producer relationships in oil fields: from hybrid constrained nonlinear optimization to inference in probabilistic graphical model. [Internet] [Doctoral dissertation]. University of Southern California; 2010. [cited 2021 May 09]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/367302/rec/4917.

Council of Science Editors:

Lee H. Parameter estimation to infer injector-producer relationships in oil fields: from hybrid constrained nonlinear optimization to inference in probabilistic graphical model. [Doctoral Dissertation]. University of Southern California; 2010. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/367302/rec/4917

25. Serrano Martínez-Santos, Nicolás. Interactive Transcription of Old Text Documents .

Degree: 2014, Universitat Politècnica de València

 Nowadays, there are huge collections of handwritten text documents in libraries all over the world. The high demand for these resources has led to the… (more)

Subjects/Keywords: Handwriting recognition; Computer-assisted annotation; Active learning; Semi-supervised learning; Confidence measures; Constrained Viterbi search; Accuracy predictio

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Serrano Martínez-Santos, N. (2014). Interactive Transcription of Old Text Documents . (Doctoral Dissertation). Universitat Politècnica de València. Retrieved from http://hdl.handle.net/10251/37979

Chicago Manual of Style (16th Edition):

Serrano Martínez-Santos, Nicolás. “Interactive Transcription of Old Text Documents .” 2014. Doctoral Dissertation, Universitat Politècnica de València. Accessed May 09, 2021. http://hdl.handle.net/10251/37979.

MLA Handbook (7th Edition):

Serrano Martínez-Santos, Nicolás. “Interactive Transcription of Old Text Documents .” 2014. Web. 09 May 2021.

Vancouver:

Serrano Martínez-Santos N. Interactive Transcription of Old Text Documents . [Internet] [Doctoral dissertation]. Universitat Politècnica de València; 2014. [cited 2021 May 09]. Available from: http://hdl.handle.net/10251/37979.

Council of Science Editors:

Serrano Martínez-Santos N. Interactive Transcription of Old Text Documents . [Doctoral Dissertation]. Universitat Politècnica de València; 2014. Available from: http://hdl.handle.net/10251/37979

26. Lindgren, Jennifer. Evaluating Hierarchical LDA Topic Models for Article Categorization.

Degree: Computer and Information Science, 2020, Linköping University

  With the vast amount of information available on the Internet today, helping users find relevant content has become a prioritized task in many software… (more)

Subjects/Keywords: topic modeling; topic models; lda; latent dirichlet allocation; hlda; hierarchical latent dirichlet allocation; constrained lda; constrained latent dirichlet allocation; news articles; categorization; machine learning; natural language processing; nlp; news recommendations; Language Technology (Computational Linguistics); Språkteknologi (språkvetenskaplig databehandling)

constrained hLDA models. It is also the algorithm used in this thesis, and the details are explained… …similarity is used in this thesis to evaluate and compare a hLDA and a constrained hLDA topic model… …outperforms hLDA with regard to this metric. In addition to this, the aim is also that the result… …document in the corpus is used as a parameter for the model. This means that the number of… …this convenient fact, the Dirichlet distribution is often used in combination with… 

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APA (6th Edition):

Lindgren, J. (2020). Evaluating Hierarchical LDA Topic Models for Article Categorization. (Thesis). Linköping University. Retrieved from http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-167080

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Lindgren, Jennifer. “Evaluating Hierarchical LDA Topic Models for Article Categorization.” 2020. Thesis, Linköping University. Accessed May 09, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-167080.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Lindgren, Jennifer. “Evaluating Hierarchical LDA Topic Models for Article Categorization.” 2020. Web. 09 May 2021.

Vancouver:

Lindgren J. Evaluating Hierarchical LDA Topic Models for Article Categorization. [Internet] [Thesis]. Linköping University; 2020. [cited 2021 May 09]. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-167080.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Lindgren J. Evaluating Hierarchical LDA Topic Models for Article Categorization. [Thesis]. Linköping University; 2020. Available from: http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-167080

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of California – San Diego

27. Babaeian, Amir. Part I - Constrained Shortest-Path For Manifold Learning And Multiple Manifold Clustering Part II - Community Detection In Large Graphs; Analysis, Design And Implementation.

Degree: Mathematics, 2017, University of California – San Diego

 In Part I of this thesis, we address the problem of manifold learning and clustering by introducing a novel constrained shortest-path algorithm. In the case… (more)

Subjects/Keywords: Mathematics; Statistics; Computer science; Community Detection; Constrained-Shortest-Path; Large Graphs; Manifold Learning; MapReduce; Multiple Manifold Clustering

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Babaeian, A. (2017). Part I - Constrained Shortest-Path For Manifold Learning And Multiple Manifold Clustering Part II - Community Detection In Large Graphs; Analysis, Design And Implementation. (Thesis). University of California – San Diego. Retrieved from http://www.escholarship.org/uc/item/4w64w79x

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Babaeian, Amir. “Part I - Constrained Shortest-Path For Manifold Learning And Multiple Manifold Clustering Part II - Community Detection In Large Graphs; Analysis, Design And Implementation.” 2017. Thesis, University of California – San Diego. Accessed May 09, 2021. http://www.escholarship.org/uc/item/4w64w79x.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Babaeian, Amir. “Part I - Constrained Shortest-Path For Manifold Learning And Multiple Manifold Clustering Part II - Community Detection In Large Graphs; Analysis, Design And Implementation.” 2017. Web. 09 May 2021.

Vancouver:

Babaeian A. Part I - Constrained Shortest-Path For Manifold Learning And Multiple Manifold Clustering Part II - Community Detection In Large Graphs; Analysis, Design And Implementation. [Internet] [Thesis]. University of California – San Diego; 2017. [cited 2021 May 09]. Available from: http://www.escholarship.org/uc/item/4w64w79x.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Babaeian A. Part I - Constrained Shortest-Path For Manifold Learning And Multiple Manifold Clustering Part II - Community Detection In Large Graphs; Analysis, Design And Implementation. [Thesis]. University of California – San Diego; 2017. Available from: http://www.escholarship.org/uc/item/4w64w79x

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Manchester

28. Allmendinger, Richard. Tuning evolutionary search for closed-loop optimization.

Degree: PhD, 2012, University of Manchester

 Closed-loop optimization deals with problems in which candidate solutions are evaluated by conducting experiments, e.g. physical or biochemical experiments. Although this form of optimization is(more)

Subjects/Keywords: 519.6; Optimization; Closed-loop optimization; Evolutionary computation; Constrained optimization; Dynamic optimization; Reinforcement learning; Adaptation; Bandit algorithms

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APA (6th Edition):

Allmendinger, R. (2012). Tuning evolutionary search for closed-loop optimization. (Doctoral Dissertation). University of Manchester. Retrieved from https://www.research.manchester.ac.uk/portal/en/theses/tuning-evolutionary-search-for-closedloop-optimization(d54e63e2-7927-42aa-b974-c41e717298cb).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.553386

Chicago Manual of Style (16th Edition):

Allmendinger, Richard. “Tuning evolutionary search for closed-loop optimization.” 2012. Doctoral Dissertation, University of Manchester. Accessed May 09, 2021. https://www.research.manchester.ac.uk/portal/en/theses/tuning-evolutionary-search-for-closedloop-optimization(d54e63e2-7927-42aa-b974-c41e717298cb).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.553386.

MLA Handbook (7th Edition):

Allmendinger, Richard. “Tuning evolutionary search for closed-loop optimization.” 2012. Web. 09 May 2021.

Vancouver:

Allmendinger R. Tuning evolutionary search for closed-loop optimization. [Internet] [Doctoral dissertation]. University of Manchester; 2012. [cited 2021 May 09]. Available from: https://www.research.manchester.ac.uk/portal/en/theses/tuning-evolutionary-search-for-closedloop-optimization(d54e63e2-7927-42aa-b974-c41e717298cb).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.553386.

Council of Science Editors:

Allmendinger R. Tuning evolutionary search for closed-loop optimization. [Doctoral Dissertation]. University of Manchester; 2012. Available from: https://www.research.manchester.ac.uk/portal/en/theses/tuning-evolutionary-search-for-closedloop-optimization(d54e63e2-7927-42aa-b974-c41e717298cb).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.553386


Queens University

29. Aliyari Ghassabeh, Youness. On the Convergence and Applications of Mean Shift Type Algorithms .

Degree: Mathematics and Statistics, 2013, Queens University

 Mean shift (MS) and subspace constrained mean shift (SCMS) algorithms are non-parametric, iterative methods to find a representation of a high dimensional data set on… (more)

Subjects/Keywords: Subspace constrained mean shift algorithm ; Noisy source vector quantization ; Dimensionality reduction ; Principal curve ; Unsupervised learning ; Convergence ; Principal surface ; Mean shift algorithm

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Aliyari Ghassabeh, Y. (2013). On the Convergence and Applications of Mean Shift Type Algorithms . (Thesis). Queens University. Retrieved from http://hdl.handle.net/1974/8365

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Aliyari Ghassabeh, Youness. “On the Convergence and Applications of Mean Shift Type Algorithms .” 2013. Thesis, Queens University. Accessed May 09, 2021. http://hdl.handle.net/1974/8365.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Aliyari Ghassabeh, Youness. “On the Convergence and Applications of Mean Shift Type Algorithms .” 2013. Web. 09 May 2021.

Vancouver:

Aliyari Ghassabeh Y. On the Convergence and Applications of Mean Shift Type Algorithms . [Internet] [Thesis]. Queens University; 2013. [cited 2021 May 09]. Available from: http://hdl.handle.net/1974/8365.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Aliyari Ghassabeh Y. On the Convergence and Applications of Mean Shift Type Algorithms . [Thesis]. Queens University; 2013. Available from: http://hdl.handle.net/1974/8365

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation


University of Washington

30. Miljanic, Veljko. Using External Knowledge to Improve Brown Clustering.

Degree: 2021, University of Washington

 In recent years, semi-supervised learning methods that rely on using low-dimensional word representation gained interest in NLP, due to their ability take advantage of vastly… (more)

Subjects/Keywords: brown clustering; constrained clustering; ner; semi-supervised learning; word representations; Linguistics; Computer science; Artificial intelligence; Linguistics

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Miljanic, V. (2021). Using External Knowledge to Improve Brown Clustering. (Thesis). University of Washington. Retrieved from http://hdl.handle.net/1773/46828

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Miljanic, Veljko. “Using External Knowledge to Improve Brown Clustering.” 2021. Thesis, University of Washington. Accessed May 09, 2021. http://hdl.handle.net/1773/46828.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Miljanic, Veljko. “Using External Knowledge to Improve Brown Clustering.” 2021. Web. 09 May 2021.

Vancouver:

Miljanic V. Using External Knowledge to Improve Brown Clustering. [Internet] [Thesis]. University of Washington; 2021. [cited 2021 May 09]. Available from: http://hdl.handle.net/1773/46828.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Miljanic V. Using External Knowledge to Improve Brown Clustering. [Thesis]. University of Washington; 2021. Available from: http://hdl.handle.net/1773/46828

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

[1] [2]

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