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University of Alberta

1.
Cheng, Hao.
*Bregman**Divergence* Clustering: A Convex Approach.

Degree: MS, Department of Computing Science, 2013, University of Alberta

URL: https://era.library.ualberta.ca/files/6d56zz264

► Due to its wide application in various fields, clustering, as a fundamental unsupervised learning problem, has been intensively investigated over the past few decades. Unfortunately,…
(more)

Subjects/Keywords: convex; clustering; Bregman divergence

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

APA (6^{th} Edition):

Cheng, H. (2013). Bregman Divergence Clustering: A Convex Approach. (Masters Thesis). University of Alberta. Retrieved from https://era.library.ualberta.ca/files/6d56zz264

Chicago Manual of Style (16^{th} Edition):

Cheng, Hao. “Bregman Divergence Clustering: A Convex Approach.” 2013. Masters Thesis, University of Alberta. Accessed July 18, 2019. https://era.library.ualberta.ca/files/6d56zz264.

MLA Handbook (7^{th} Edition):

Cheng, Hao. “Bregman Divergence Clustering: A Convex Approach.” 2013. Web. 18 Jul 2019.

Vancouver:

Cheng H. Bregman Divergence Clustering: A Convex Approach. [Internet] [Masters thesis]. University of Alberta; 2013. [cited 2019 Jul 18]. Available from: https://era.library.ualberta.ca/files/6d56zz264.

Council of Science Editors:

Cheng H. Bregman Divergence Clustering: A Convex Approach. [Masters Thesis]. University of Alberta; 2013. Available from: https://era.library.ualberta.ca/files/6d56zz264

Princeton University

2. Basbug, Mehmet Emin. Integrating Exponential Dispersion Models to Latent Structures .

Degree: PhD, 2017, Princeton University

URL: http://arks.princeton.edu/ark:/88435/dsp019z903235x

► Latent variable models have two basic components: a latent structure encoding a hypothesized complex pattern and an observation model capturing the data distribution. With the…
(more)

Subjects/Keywords: Bregman Divergence; Clustering; Exponential Dispersion Model; Machine Learning; Matrix Factorization; Missing Data

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APA (6^{th} Edition):

Basbug, M. E. (2017). Integrating Exponential Dispersion Models to Latent Structures . (Doctoral Dissertation). Princeton University. Retrieved from http://arks.princeton.edu/ark:/88435/dsp019z903235x

Chicago Manual of Style (16^{th} Edition):

Basbug, Mehmet Emin. “Integrating Exponential Dispersion Models to Latent Structures .” 2017. Doctoral Dissertation, Princeton University. Accessed July 18, 2019. http://arks.princeton.edu/ark:/88435/dsp019z903235x.

MLA Handbook (7^{th} Edition):

Basbug, Mehmet Emin. “Integrating Exponential Dispersion Models to Latent Structures .” 2017. Web. 18 Jul 2019.

Vancouver:

Basbug ME. Integrating Exponential Dispersion Models to Latent Structures . [Internet] [Doctoral dissertation]. Princeton University; 2017. [cited 2019 Jul 18]. Available from: http://arks.princeton.edu/ark:/88435/dsp019z903235x.

Council of Science Editors:

Basbug ME. Integrating Exponential Dispersion Models to Latent Structures . [Doctoral Dissertation]. Princeton University; 2017. Available from: http://arks.princeton.edu/ark:/88435/dsp019z903235x

Western Michigan University

3.
Abdullah, Osamah Ali.
Indoor Localization of Mobile Devices Based on Wi-Fi Signals Via Convex Optimization and *Bregman* * Divergence*.

Degree: PhD, Electrical and Computer Engineering, 2016, Western Michigan University

URL: https://scholarworks.wmich.edu/dissertations/2497

► Indoor positioning systems (IPS) have been the *subject* of intense academic and industrial research due to the significance of such systems in a wide…
(more)

Subjects/Keywords: Bregman divergence; PIIN; KNN; Wi-Fi; fingerprint; KLnrg; Electrical and Computer Engineering

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APA (6^{th} Edition):

Abdullah, O. A. (2016). Indoor Localization of Mobile Devices Based on Wi-Fi Signals Via Convex Optimization and Bregman Divergence. (Doctoral Dissertation). Western Michigan University. Retrieved from https://scholarworks.wmich.edu/dissertations/2497

Chicago Manual of Style (16^{th} Edition):

Abdullah, Osamah Ali. “Indoor Localization of Mobile Devices Based on Wi-Fi Signals Via Convex Optimization and Bregman Divergence.” 2016. Doctoral Dissertation, Western Michigan University. Accessed July 18, 2019. https://scholarworks.wmich.edu/dissertations/2497.

MLA Handbook (7^{th} Edition):

Abdullah, Osamah Ali. “Indoor Localization of Mobile Devices Based on Wi-Fi Signals Via Convex Optimization and Bregman Divergence.” 2016. Web. 18 Jul 2019.

Vancouver:

Abdullah OA. Indoor Localization of Mobile Devices Based on Wi-Fi Signals Via Convex Optimization and Bregman Divergence. [Internet] [Doctoral dissertation]. Western Michigan University; 2016. [cited 2019 Jul 18]. Available from: https://scholarworks.wmich.edu/dissertations/2497.

Council of Science Editors:

Abdullah OA. Indoor Localization of Mobile Devices Based on Wi-Fi Signals Via Convex Optimization and Bregman Divergence. [Doctoral Dissertation]. Western Michigan University; 2016. Available from: https://scholarworks.wmich.edu/dissertations/2497

University of Minnesota

4. Cherian, Anoop. Similarity search in visual data.

Degree: PhD, Computer science, 2013, University of Minnesota

URL: http://purl.umn.edu/144455

► Contemporary times have witnessed a significant increase in the amount of data available on the Internet. Organizing such big data so that it is easily…
(more)

Subjects/Keywords: Covariance matrices; Dictionary learning; Dirichlet process; Jensen-bregman logdet divergence; Nearest neighbors; Sparse coding

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

APA (6^{th} Edition):

Cherian, A. (2013). Similarity search in visual data. (Doctoral Dissertation). University of Minnesota. Retrieved from http://purl.umn.edu/144455

Chicago Manual of Style (16^{th} Edition):

Cherian, Anoop. “Similarity search in visual data.” 2013. Doctoral Dissertation, University of Minnesota. Accessed July 18, 2019. http://purl.umn.edu/144455.

MLA Handbook (7^{th} Edition):

Cherian, Anoop. “Similarity search in visual data.” 2013. Web. 18 Jul 2019.

Vancouver:

Cherian A. Similarity search in visual data. [Internet] [Doctoral dissertation]. University of Minnesota; 2013. [cited 2019 Jul 18]. Available from: http://purl.umn.edu/144455.

Council of Science Editors:

Cherian A. Similarity search in visual data. [Doctoral Dissertation]. University of Minnesota; 2013. Available from: http://purl.umn.edu/144455

5. Acharyya, Sreangsu. Learning to rank in supervised and unsupervised settings using convexity and monotonicity.

Degree: Electrical and Computer Engineering, 2013, University of Texas – Austin

URL: http://hdl.handle.net/2152/21154

► This dissertation addresses the task of learning to rank, both in the supervised and unsupervised settings, by exploiting the interplay of convex functions, monotonic mappings…
(more)

Subjects/Keywords: Learning to rank; Convexity; Monotonicity; Bregman divergence

…*Bregman* *divergence* between the consensus rank and the ranks induced by item specific… …7
2.2
*Bregman* *Divergence* . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
9… …such that the symmetrized *Bregman* *divergence* between ρT and wT +1
is
5.4
β
1−β
times their… …schematic applies equally to the general *Bregman* *divergence* case as well. To represent this… …simultaneous projections can be computed independent of the *Bregman* *divergence* and
the other…

Record Details Similar Records

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

APA (6^{th} Edition):

Acharyya, S. (2013). Learning to rank in supervised and unsupervised settings using convexity and monotonicity. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/21154

Note: this citation may be lacking information needed for this citation format:

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Acharyya, Sreangsu. “Learning to rank in supervised and unsupervised settings using convexity and monotonicity.” 2013. Thesis, University of Texas – Austin. Accessed July 18, 2019. http://hdl.handle.net/2152/21154.

Note: this citation may be lacking information needed for this citation format:

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Acharyya, Sreangsu. “Learning to rank in supervised and unsupervised settings using convexity and monotonicity.” 2013. Web. 18 Jul 2019.

Vancouver:

Acharyya S. Learning to rank in supervised and unsupervised settings using convexity and monotonicity. [Internet] [Thesis]. University of Texas – Austin; 2013. [cited 2019 Jul 18]. Available from: http://hdl.handle.net/2152/21154.

Note: this citation may be lacking information needed for this citation format:

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Acharyya S. Learning to rank in supervised and unsupervised settings using convexity and monotonicity. [Thesis]. University of Texas – Austin; 2013. Available from: http://hdl.handle.net/2152/21154

Not specified: Masters Thesis or Doctoral Dissertation

Pontifical Catholic University of Rio de Janeiro

6.
DANIEL ALEJANDRO MESEJO-LEON.
[en] APPROXIMATE NEAREST NEIGHBOR SEARCH FOR THE
KULLBACK-LEIBLER * DIVERGENCE*.

Degree: 2018, Pontifical Catholic University of Rio de Janeiro

URL: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=33305

►

[pt] Em uma série de aplicações, os pontos de dados podem ser representados como distribuições de probabilidade. Por exemplo, os documentos podem ser representados como… (more)

Subjects/Keywords: [pt] DIVERGENCIA KULLBACK-LEIBER; [en] KULLBACK-LEIBLER DIVERGENCE; [pt] BUSCA DE VIZINHOS MAIS PROXIMOS; [en] NEAREST NEIGHBOR SEARCH; [pt] INDICES INVERTIDOS; [en] INVERTED INDEX; [pt] HASH SENSIVEL A LOCALIDADE; [en] LOCALITY SENSITIVE HASHING; [pt] ARVORES DE BREGMAN; [en] BREGMAN BALL TREE

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

APA (6^{th} Edition):

MESEJO-LEON, D. A. (2018). [en] APPROXIMATE NEAREST NEIGHBOR SEARCH FOR THE KULLBACK-LEIBLER DIVERGENCE. (Thesis). Pontifical Catholic University of Rio de Janeiro. Retrieved from http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=33305

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

MESEJO-LEON, DANIEL ALEJANDRO. “[en] APPROXIMATE NEAREST NEIGHBOR SEARCH FOR THE KULLBACK-LEIBLER DIVERGENCE.” 2018. Thesis, Pontifical Catholic University of Rio de Janeiro. Accessed July 18, 2019. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=33305.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

MESEJO-LEON, DANIEL ALEJANDRO. “[en] APPROXIMATE NEAREST NEIGHBOR SEARCH FOR THE KULLBACK-LEIBLER DIVERGENCE.” 2018. Web. 18 Jul 2019.

Vancouver:

MESEJO-LEON DA. [en] APPROXIMATE NEAREST NEIGHBOR SEARCH FOR THE KULLBACK-LEIBLER DIVERGENCE. [Internet] [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2018. [cited 2019 Jul 18]. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=33305.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

MESEJO-LEON DA. [en] APPROXIMATE NEAREST NEIGHBOR SEARCH FOR THE KULLBACK-LEIBLER DIVERGENCE. [Thesis]. Pontifical Catholic University of Rio de Janeiro; 2018. Available from: http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=33305

Not specified: Masters Thesis or Doctoral Dissertation

University of Florida

7.
Liu, Meizhu.
Total *Bregman* *Divergence*, a Robust *Divergence* Measure, and Its Applications.

Degree: PhD, Computer Engineering - Computer and Information Science and Engineering, 2011, University of Florida

URL: http://ufdc.ufl.edu/UFE0043601

► *Divergence* measures provide a means to measure the pairwise dissimilarity between "objects", e.g., vectors and probability density functions (pdfs). Kullback-Leibler (KL) *divergence* and the square…
(more)

Subjects/Keywords: Algorithms; Computer conferencing; Computer pattern recognition; Computer vision; Databases; Datasets; Information retrieval; Machine learning; Outliers; Tensors; boosting – bregman – divergence – dti – metric – robust

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

APA (6^{th} Edition):

Liu, M. (2011). Total Bregman Divergence, a Robust Divergence Measure, and Its Applications. (Doctoral Dissertation). University of Florida. Retrieved from http://ufdc.ufl.edu/UFE0043601

Chicago Manual of Style (16^{th} Edition):

Liu, Meizhu. “Total Bregman Divergence, a Robust Divergence Measure, and Its Applications.” 2011. Doctoral Dissertation, University of Florida. Accessed July 18, 2019. http://ufdc.ufl.edu/UFE0043601.

MLA Handbook (7^{th} Edition):

Liu, Meizhu. “Total Bregman Divergence, a Robust Divergence Measure, and Its Applications.” 2011. Web. 18 Jul 2019.

Vancouver:

Liu M. Total Bregman Divergence, a Robust Divergence Measure, and Its Applications. [Internet] [Doctoral dissertation]. University of Florida; 2011. [cited 2019 Jul 18]. Available from: http://ufdc.ufl.edu/UFE0043601.

Council of Science Editors:

Liu M. Total Bregman Divergence, a Robust Divergence Measure, and Its Applications. [Doctoral Dissertation]. University of Florida; 2011. Available from: http://ufdc.ufl.edu/UFE0043601

8. Hasnat, Md Abul. Unsupervised 3D image clustering and extension to joint color and depth segmentation : Classification non supervisée d’images 3D et extension à la segmentation exploitant les informations de couleur et de profondeur.

Degree: Docteur es, Image, Vision, Signal, 2014, Saint-Etienne

URL: http://www.theses.fr/2014STET4013

►

L'accès aux séquences d'images 3D s'est aujourd'hui démocratisé, grâce aux récentes avancées dans le développement des capteurs de profondeur ainsi que des méthodes permettant de… (more)

Subjects/Keywords: Analyse d'images de profondeur; Segmentation d'images RGB-D; Classification non supervisée; Divergence de Bregman; Sélection de modèles; Distributions directionnelles; Loi de Von Mises-Fisher; Loi de Watson; Analysis depth images; RGB-D image segmentation; Unsupervised classification; Bregman divergence; Models selection; Directional distributions; Von Mises-Fisher distribution; Watson distribution

Record Details Similar Records

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

APA (6^{th} Edition):

Hasnat, M. A. (2014). Unsupervised 3D image clustering and extension to joint color and depth segmentation : Classification non supervisée d’images 3D et extension à la segmentation exploitant les informations de couleur et de profondeur. (Doctoral Dissertation). Saint-Etienne. Retrieved from http://www.theses.fr/2014STET4013

Chicago Manual of Style (16^{th} Edition):

Hasnat, Md Abul. “Unsupervised 3D image clustering and extension to joint color and depth segmentation : Classification non supervisée d’images 3D et extension à la segmentation exploitant les informations de couleur et de profondeur.” 2014. Doctoral Dissertation, Saint-Etienne. Accessed July 18, 2019. http://www.theses.fr/2014STET4013.

MLA Handbook (7^{th} Edition):

Hasnat, Md Abul. “Unsupervised 3D image clustering and extension to joint color and depth segmentation : Classification non supervisée d’images 3D et extension à la segmentation exploitant les informations de couleur et de profondeur.” 2014. Web. 18 Jul 2019.

Vancouver:

Hasnat MA. Unsupervised 3D image clustering and extension to joint color and depth segmentation : Classification non supervisée d’images 3D et extension à la segmentation exploitant les informations de couleur et de profondeur. [Internet] [Doctoral dissertation]. Saint-Etienne; 2014. [cited 2019 Jul 18]. Available from: http://www.theses.fr/2014STET4013.

Council of Science Editors:

Hasnat MA. Unsupervised 3D image clustering and extension to joint color and depth segmentation : Classification non supervisée d’images 3D et extension à la segmentation exploitant les informations de couleur et de profondeur. [Doctoral Dissertation]. Saint-Etienne; 2014. Available from: http://www.theses.fr/2014STET4013

9. Adamcik, Martin. Collective reasoning under uncertainty and inconsistency.

Degree: PhD, 2014, University of Manchester

URL: https://www.research.manchester.ac.uk/portal/en/theses/collective-reasoning-under-uncertainty-and-inconsistency(7fab8021-8beb-45e7-8b45-7cb4fadd70be).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.603220

► In this thesis we investigate some global desiderata for probabilistic knowledge merging given several possibly jointly inconsistent, but individually consistent knowledge bases. We show that…
(more)

Subjects/Keywords: 519.2; probabilistic reasoning; probability function; probabilistic merging; Bregman divergence; Kullback-Leibler divergence; principles for merging

Record Details Similar Records

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

APA (6^{th} Edition):

Adamcik, M. (2014). Collective reasoning under uncertainty and inconsistency. (Doctoral Dissertation). University of Manchester. Retrieved from https://www.research.manchester.ac.uk/portal/en/theses/collective-reasoning-under-uncertainty-and-inconsistency(7fab8021-8beb-45e7-8b45-7cb4fadd70be).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.603220

Chicago Manual of Style (16^{th} Edition):

Adamcik, Martin. “Collective reasoning under uncertainty and inconsistency.” 2014. Doctoral Dissertation, University of Manchester. Accessed July 18, 2019. https://www.research.manchester.ac.uk/portal/en/theses/collective-reasoning-under-uncertainty-and-inconsistency(7fab8021-8beb-45e7-8b45-7cb4fadd70be).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.603220.

MLA Handbook (7^{th} Edition):

Adamcik, Martin. “Collective reasoning under uncertainty and inconsistency.” 2014. Web. 18 Jul 2019.

Vancouver:

Adamcik M. Collective reasoning under uncertainty and inconsistency. [Internet] [Doctoral dissertation]. University of Manchester; 2014. [cited 2019 Jul 18]. Available from: https://www.research.manchester.ac.uk/portal/en/theses/collective-reasoning-under-uncertainty-and-inconsistency(7fab8021-8beb-45e7-8b45-7cb4fadd70be).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.603220.

Council of Science Editors:

Adamcik M. Collective reasoning under uncertainty and inconsistency. [Doctoral Dissertation]. University of Manchester; 2014. Available from: https://www.research.manchester.ac.uk/portal/en/theses/collective-reasoning-under-uncertainty-and-inconsistency(7fab8021-8beb-45e7-8b45-7cb4fadd70be).html ; http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.603220

10. Adamcik, Martin. Collective Reasoning under Uncertainty and Inconsistency.

Degree: 2014, University of Manchester

URL: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:219828

► In this thesis we investigate some global desiderata for probabilistic knowledge merging given several possibly jointly inconsistent, but individually consistent knowledge bases. We show that…
(more)

Subjects/Keywords: probabilistic reasoning; probability function; probabilistic merging; Bregman divergence; Kullback-Leibler divergence; principles for merging

Record Details Similar Records

❌

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

APA (6^{th} Edition):

Adamcik, M. (2014). Collective Reasoning under Uncertainty and Inconsistency. (Doctoral Dissertation). University of Manchester. Retrieved from http://www.manchester.ac.uk/escholar/uk-ac-man-scw:219828

Chicago Manual of Style (16^{th} Edition):

Adamcik, Martin. “Collective Reasoning under Uncertainty and Inconsistency.” 2014. Doctoral Dissertation, University of Manchester. Accessed July 18, 2019. http://www.manchester.ac.uk/escholar/uk-ac-man-scw:219828.

MLA Handbook (7^{th} Edition):

Adamcik, Martin. “Collective Reasoning under Uncertainty and Inconsistency.” 2014. Web. 18 Jul 2019.

Vancouver:

Adamcik M. Collective Reasoning under Uncertainty and Inconsistency. [Internet] [Doctoral dissertation]. University of Manchester; 2014. [cited 2019 Jul 18]. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:219828.

Council of Science Editors:

Adamcik M. Collective Reasoning under Uncertainty and Inconsistency. [Doctoral Dissertation]. University of Manchester; 2014. Available from: http://www.manchester.ac.uk/escholar/uk-ac-man-scw:219828

11. Sustik, Mátyás Attila. Structured numerical problems in contemporary applications.

Degree: Computer Sciences, 2013, University of Texas – Austin

URL: http://hdl.handle.net/2152/21855

► The presence of structure in a computational problem can often be exploited and can lead to a more efficient numerical algorithm. In this dissertation, we…
(more)

Subjects/Keywords: Matrix computation; Inverse eigenvalue problem; Equiangular frame; Bregman divergence; Zero-finding; Divide-and-conquer eigensolver

…*divergence*, and Cholesky updates in case of the
LogDet *Bregman* matrix *divergence*. Our contribution… …the objective functions to be minimized
are the von Neumann and the LogDet *Bregman* matrix… …4.1.3 Bregman’s Algorithm . . . . . . . . . . . . .
4.2 *Bregman* Divergences for Rank–deficient… …Kernel Learning with *Bregman* Matrix Divergences
with B. Kulis and I. S. Dhillon appeared in…

Record Details Similar Records

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

APA (6^{th} Edition):

Sustik, M. A. (2013). Structured numerical problems in contemporary applications. (Thesis). University of Texas – Austin. Retrieved from http://hdl.handle.net/2152/21855

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Sustik, Mátyás Attila. “Structured numerical problems in contemporary applications.” 2013. Thesis, University of Texas – Austin. Accessed July 18, 2019. http://hdl.handle.net/2152/21855.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Sustik, Mátyás Attila. “Structured numerical problems in contemporary applications.” 2013. Web. 18 Jul 2019.

Vancouver:

Sustik MA. Structured numerical problems in contemporary applications. [Internet] [Thesis]. University of Texas – Austin; 2013. [cited 2019 Jul 18]. Available from: http://hdl.handle.net/2152/21855.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Sustik MA. Structured numerical problems in contemporary applications. [Thesis]. University of Texas – Austin; 2013. Available from: http://hdl.handle.net/2152/21855

Not specified: Masters Thesis or Doctoral Dissertation

12. Sears, Timothy. Generalized Maximum Entropy, Convexity and Machine Learning .

Degree: 2010, Australian National University

URL: http://hdl.handle.net/1885/49355

► This thesis identiﬁes and extends techniques that can be linked to the principle of maximum entropy (maxent) and applied to parameter estimation in machine learning…
(more)

Subjects/Keywords: Maximum entropy; Bregman divergence; exponential family; deformed logarithm; escort distribution; non-negative matrix factorization.

…NMF).
Keywords: Maximum entropy, *Bregman* *divergence*, exponential family, deformed… …Examples . . . . . . . . . . . . . . .
2.3 *Bregman* *Divergence*… …2.3.1 Support function of *Bregman* *divergence* sublevel set
2.3.2 Csiszar’s *divergence*… …sets. . . . . . . . . . . . . . . . . .
*Bregman* *divergence* . . . . . . . . . . . . .
*Bregman*… …turn a special case of *Bregman* *divergence*. *Bregman* *divergence* between two distributions is…

Record Details Similar Records

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

APA (6^{th} Edition):

Sears, T. (2010). Generalized Maximum Entropy, Convexity and Machine Learning . (Thesis). Australian National University. Retrieved from http://hdl.handle.net/1885/49355

Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16^{th} Edition):

Sears, Timothy. “Generalized Maximum Entropy, Convexity and Machine Learning .” 2010. Thesis, Australian National University. Accessed July 18, 2019. http://hdl.handle.net/1885/49355.

Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7^{th} Edition):

Sears, Timothy. “Generalized Maximum Entropy, Convexity and Machine Learning .” 2010. Web. 18 Jul 2019.

Vancouver:

Sears T. Generalized Maximum Entropy, Convexity and Machine Learning . [Internet] [Thesis]. Australian National University; 2010. [cited 2019 Jul 18]. Available from: http://hdl.handle.net/1885/49355.

Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Sears T. Generalized Maximum Entropy, Convexity and Machine Learning . [Thesis]. Australian National University; 2010. Available from: http://hdl.handle.net/1885/49355

Not specified: Masters Thesis or Doctoral Dissertation