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You searched for +publisher:"University of Southern California" +contributor:("Liu, Yan"). Showing records 1 – 15 of 15 total matches.

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University of Southern California

1. Zhang, Mi. Ubiquitous computing for human activity analysis with applications in personalized healthcare.

Degree: PhD, Computer Engineering, 2013, University of Southern California

 Ubiquitous computing envisions a world in which people can access computing resources anywhere and any time. Over the past decade, the emergence and availability of… (more)

Subjects/Keywords: human activity recognition; mobile computing; personalized healthcare; ubiquitous computing; virtual rehabilitation; wireless health

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APA (6th Edition):

Zhang, M. (2013). Ubiquitous computing for human activity analysis with applications in personalized healthcare. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/283085/rec/7640

Chicago Manual of Style (16th Edition):

Zhang, Mi. “Ubiquitous computing for human activity analysis with applications in personalized healthcare.” 2013. Doctoral Dissertation, University of Southern California. Accessed February 27, 2020. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/283085/rec/7640.

MLA Handbook (7th Edition):

Zhang, Mi. “Ubiquitous computing for human activity analysis with applications in personalized healthcare.” 2013. Web. 27 Feb 2020.

Vancouver:

Zhang M. Ubiquitous computing for human activity analysis with applications in personalized healthcare. [Internet] [Doctoral dissertation]. University of Southern California; 2013. [cited 2020 Feb 27]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/283085/rec/7640.

Council of Science Editors:

Zhang M. Ubiquitous computing for human activity analysis with applications in personalized healthcare. [Doctoral Dissertation]. University of Southern California; 2013. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/283085/rec/7640


University of Southern California

2. Sheng, Lingyan. Novel algorithms for large scale supervised and one class learning.

Degree: PhD, Electrical Engineering, 2013, University of Southern California

 Supervised learning is the machine learning task of inferring a function from labeled training data. There have been numerous algorithms proposed for supervised learning, such… (more)

Subjects/Keywords: supervised learning; one class learning; linear discriminant analysis; graph; Nyströ; m approximation

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APA (6th Edition):

Sheng, L. (2013). Novel algorithms for large scale supervised and one class learning. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/225861/rec/4459

Chicago Manual of Style (16th Edition):

Sheng, Lingyan. “Novel algorithms for large scale supervised and one class learning.” 2013. Doctoral Dissertation, University of Southern California. Accessed February 27, 2020. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/225861/rec/4459.

MLA Handbook (7th Edition):

Sheng, Lingyan. “Novel algorithms for large scale supervised and one class learning.” 2013. Web. 27 Feb 2020.

Vancouver:

Sheng L. Novel algorithms for large scale supervised and one class learning. [Internet] [Doctoral dissertation]. University of Southern California; 2013. [cited 2020 Feb 27]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/225861/rec/4459.

Council of Science Editors:

Sheng L. Novel algorithms for large scale supervised and one class learning. [Doctoral Dissertation]. University of Southern California; 2013. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/225861/rec/4459


University of Southern California

3. Tseng, Po-He. Eye-trace signatures of clinical populations under natural viewing.

Degree: PhD, Computer Science, 2012, University of Southern California

 A significant problem in clinical diagnosis of certain neurobehavioral disorders is the overlap in observed behavioral deficits, which extensively complicates diagnosis by requiring additional neuropsychometric… (more)

Subjects/Keywords: attention deficits hyperactivity disorder; eye movements; fetal alcohol spectrum disorder; machine learning; natural scenes; Parkinson'; s disease

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APA (6th Edition):

Tseng, P. (2012). Eye-trace signatures of clinical populations under natural viewing. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/125265/rec/2694

Chicago Manual of Style (16th Edition):

Tseng, Po-He. “Eye-trace signatures of clinical populations under natural viewing.” 2012. Doctoral Dissertation, University of Southern California. Accessed February 27, 2020. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/125265/rec/2694.

MLA Handbook (7th Edition):

Tseng, Po-He. “Eye-trace signatures of clinical populations under natural viewing.” 2012. Web. 27 Feb 2020.

Vancouver:

Tseng P. Eye-trace signatures of clinical populations under natural viewing. [Internet] [Doctoral dissertation]. University of Southern California; 2012. [cited 2020 Feb 27]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/125265/rec/2694.

Council of Science Editors:

Tseng P. Eye-trace signatures of clinical populations under natural viewing. [Doctoral Dissertation]. University of Southern California; 2012. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/125265/rec/2694


University of Southern California

4. Kalathil, Dileep Manisseri. Empirical methods in control and optimization.

Degree: PhD, Electrical Engineering, 2014, University of Southern California

 This dissertation addresses some problems in the area of learning, optimization and decision making in stochastic systems using empirical methods. ❧ First part of the… (more)

Subjects/Keywords: online optimization; multi-armed bandits; MDP; approachability; spectrum sharing

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APA (6th Edition):

Kalathil, D. M. (2014). Empirical methods in control and optimization. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/489169/rec/2320

Chicago Manual of Style (16th Edition):

Kalathil, Dileep Manisseri. “Empirical methods in control and optimization.” 2014. Doctoral Dissertation, University of Southern California. Accessed February 27, 2020. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/489169/rec/2320.

MLA Handbook (7th Edition):

Kalathil, Dileep Manisseri. “Empirical methods in control and optimization.” 2014. Web. 27 Feb 2020.

Vancouver:

Kalathil DM. Empirical methods in control and optimization. [Internet] [Doctoral dissertation]. University of Southern California; 2014. [cited 2020 Feb 27]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/489169/rec/2320.

Council of Science Editors:

Kalathil DM. Empirical methods in control and optimization. [Doctoral Dissertation]. University of Southern California; 2014. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/489169/rec/2320


University of Southern California

5. Zhao, Xuemei. Motion pattern learning and applications to tracking and detection.

Degree: PhD, Electrical Engineering, 2014, University of Southern California

 With the decreasing cost of collecting data, the deluge of surveillance videos makes it necessary to carry out automatic intelligent processing to understand scenes and… (more)

Subjects/Keywords: motion pattern; tracking; detection; crowded scene; tensor voting

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APA (6th Edition):

Zhao, X. (2014). Motion pattern learning and applications to tracking and detection. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/316458/rec/4223

Chicago Manual of Style (16th Edition):

Zhao, Xuemei. “Motion pattern learning and applications to tracking and detection.” 2014. Doctoral Dissertation, University of Southern California. Accessed February 27, 2020. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/316458/rec/4223.

MLA Handbook (7th Edition):

Zhao, Xuemei. “Motion pattern learning and applications to tracking and detection.” 2014. Web. 27 Feb 2020.

Vancouver:

Zhao X. Motion pattern learning and applications to tracking and detection. [Internet] [Doctoral dissertation]. University of Southern California; 2014. [cited 2020 Feb 27]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/316458/rec/4223.

Council of Science Editors:

Zhao X. Motion pattern learning and applications to tracking and detection. [Doctoral Dissertation]. University of Southern California; 2014. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/316458/rec/4223


University of Southern California

6. Sedghi, Hanie. Stochastic optimization in high dimension.

Degree: PhD, Electrical Engineering, 2015, University of Southern California

 In this thesis, we consider two main problems in learning with big data: data integrity and high dimension. We specifically consider the problem of data… (more)

Subjects/Keywords: stochastic ADMM; l1 regularization; multi-block ADMM; sparse+low rank decomposition; convergence rate; high dimensional regime

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APA (6th Edition):

Sedghi, H. (2015). Stochastic optimization in high dimension. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/610840/rec/6068

Chicago Manual of Style (16th Edition):

Sedghi, Hanie. “Stochastic optimization in high dimension.” 2015. Doctoral Dissertation, University of Southern California. Accessed February 27, 2020. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/610840/rec/6068.

MLA Handbook (7th Edition):

Sedghi, Hanie. “Stochastic optimization in high dimension.” 2015. Web. 27 Feb 2020.

Vancouver:

Sedghi H. Stochastic optimization in high dimension. [Internet] [Doctoral dissertation]. University of Southern California; 2015. [cited 2020 Feb 27]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/610840/rec/6068.

Council of Science Editors:

Sedghi H. Stochastic optimization in high dimension. [Doctoral Dissertation]. University of Southern California; 2015. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/610840/rec/6068


University of Southern California

7. Bahadori, Mohammad Taha. Scalable multivariate time series analysis.

Degree: PhD, Electrical Engineering, 2015, University of Southern California

 Time series data have become ubiquitous in many applications such as climate science, social media, and health care. Analysis of large scale time series data… (more)

Subjects/Keywords: time series; scalability; spatio-temporal analysis; tensor; functional data analysis; subspace clustering; latent variables; irregular time series; extreme values; copula; forecasting; classification; clustering

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APA (6th Edition):

Bahadori, M. T. (2015). Scalable multivariate time series analysis. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/593708/rec/5682

Chicago Manual of Style (16th Edition):

Bahadori, Mohammad Taha. “Scalable multivariate time series analysis.” 2015. Doctoral Dissertation, University of Southern California. Accessed February 27, 2020. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/593708/rec/5682.

MLA Handbook (7th Edition):

Bahadori, Mohammad Taha. “Scalable multivariate time series analysis.” 2015. Web. 27 Feb 2020.

Vancouver:

Bahadori MT. Scalable multivariate time series analysis. [Internet] [Doctoral dissertation]. University of Southern California; 2015. [cited 2020 Feb 27]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/593708/rec/5682.

Council of Science Editors:

Bahadori MT. Scalable multivariate time series analysis. [Doctoral Dissertation]. University of Southern California; 2015. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/593708/rec/5682


University of Southern California

8. Narang, Sunil Kumar. Critically sampled wavelet filterbanks on graphs.

Degree: PhD, Electrical Engineering, 2012, University of Southern California

 Emerging data mining applications will have to operate on datasets defined on graphs. Examples of such datasets include online document networks, social networks, and transportation… (more)

Subjects/Keywords: digital signal processing; network theory (graphs); sampling in graphs; wavelet transforms

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APA (6th Edition):

Narang, S. K. (2012). Critically sampled wavelet filterbanks on graphs. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/63114/rec/1709

Chicago Manual of Style (16th Edition):

Narang, Sunil Kumar. “Critically sampled wavelet filterbanks on graphs.” 2012. Doctoral Dissertation, University of Southern California. Accessed February 27, 2020. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/63114/rec/1709.

MLA Handbook (7th Edition):

Narang, Sunil Kumar. “Critically sampled wavelet filterbanks on graphs.” 2012. Web. 27 Feb 2020.

Vancouver:

Narang SK. Critically sampled wavelet filterbanks on graphs. [Internet] [Doctoral dissertation]. University of Southern California; 2012. [cited 2020 Feb 27]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/63114/rec/1709.

Council of Science Editors:

Narang SK. Critically sampled wavelet filterbanks on graphs. [Doctoral Dissertation]. University of Southern California; 2012. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/63114/rec/1709


University of Southern California

9. Dai, Chao. Integrating high-throughput sequencing data to study gene regulation.

Degree: PhD, Computational Biology and Bioinformatics, 2015, University of Southern California

 High-throughput sequencing is a powerful technique for gene regulation study, which can provide information about isoform expression as well as transcription factors / epigenetic factors… (more)

Subjects/Keywords: gene regulation; RNA-seq; ChIP-seq; spatial genome organization

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APA (6th Edition):

Dai, C. (2015). Integrating high-throughput sequencing data to study gene regulation. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/340117/rec/3533

Chicago Manual of Style (16th Edition):

Dai, Chao. “Integrating high-throughput sequencing data to study gene regulation.” 2015. Doctoral Dissertation, University of Southern California. Accessed February 27, 2020. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/340117/rec/3533.

MLA Handbook (7th Edition):

Dai, Chao. “Integrating high-throughput sequencing data to study gene regulation.” 2015. Web. 27 Feb 2020.

Vancouver:

Dai C. Integrating high-throughput sequencing data to study gene regulation. [Internet] [Doctoral dissertation]. University of Southern California; 2015. [cited 2020 Feb 27]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/340117/rec/3533.

Council of Science Editors:

Dai C. Integrating high-throughput sequencing data to study gene regulation. [Doctoral Dissertation]. University of Southern California; 2015. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/340117/rec/3533


University of Southern California

10. Xing, Songhua. Geospatial query processing in surface and hybrid spaces.

Degree: PhD, Computer Science, 2012, University of Southern California

 The growing popularity of online Earth visualization tools and geo-realistic games and the availability of high resolution terrain data have motivated a new class of… (more)

Subjects/Keywords: hybrid space; query processing; spatial index; surface

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APA (6th Edition):

Xing, S. (2012). Geospatial query processing in surface and hybrid spaces. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/200222/rec/3036

Chicago Manual of Style (16th Edition):

Xing, Songhua. “Geospatial query processing in surface and hybrid spaces.” 2012. Doctoral Dissertation, University of Southern California. Accessed February 27, 2020. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/200222/rec/3036.

MLA Handbook (7th Edition):

Xing, Songhua. “Geospatial query processing in surface and hybrid spaces.” 2012. Web. 27 Feb 2020.

Vancouver:

Xing S. Geospatial query processing in surface and hybrid spaces. [Internet] [Doctoral dissertation]. University of Southern California; 2012. [cited 2020 Feb 27]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/200222/rec/3036.

Council of Science Editors:

Xing S. Geospatial query processing in surface and hybrid spaces. [Doctoral Dissertation]. University of Southern California; 2012. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/200222/rec/3036


University of Southern California

11. Ghosh, Rumi. Disentangling the network: understanding the interplay of topology and dynamics in network analysis.

Degree: PhD, Computer Science, 2012, University of Southern California

 Understanding the complex interplay of topology and dynamics in complex networks is necessary to answer a variety of questions, including who are the important people… (more)

Subjects/Keywords: centrality; communities; information diffusion; network analysis; network dynamics; online social networks

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APA (6th Edition):

Ghosh, R. (2012). Disentangling the network: understanding the interplay of topology and dynamics in network analysis. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/60034/rec/2036

Chicago Manual of Style (16th Edition):

Ghosh, Rumi. “Disentangling the network: understanding the interplay of topology and dynamics in network analysis.” 2012. Doctoral Dissertation, University of Southern California. Accessed February 27, 2020. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/60034/rec/2036.

MLA Handbook (7th Edition):

Ghosh, Rumi. “Disentangling the network: understanding the interplay of topology and dynamics in network analysis.” 2012. Web. 27 Feb 2020.

Vancouver:

Ghosh R. Disentangling the network: understanding the interplay of topology and dynamics in network analysis. [Internet] [Doctoral dissertation]. University of Southern California; 2012. [cited 2020 Feb 27]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/60034/rec/2036.

Council of Science Editors:

Ghosh R. Disentangling the network: understanding the interplay of topology and dynamics in network analysis. [Doctoral Dissertation]. University of Southern California; 2012. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/60034/rec/2036


University of Southern California

12. Alayed, Hashem Ali. Behavior-based approaches for detecting cheating in online games.

Degree: PhD, Computer Science, 2015, University of Southern California

 The online games industry has grown rapidly over the last decade. As a result of this rapid growth, many techniques have been created in response… (more)

Subjects/Keywords: online games; cheating detection; machine learning; classification; anomaly detection; hybrid system

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APA (6th Edition):

Alayed, H. A. (2015). Behavior-based approaches for detecting cheating in online games. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/545519/rec/1058

Chicago Manual of Style (16th Edition):

Alayed, Hashem Ali. “Behavior-based approaches for detecting cheating in online games.” 2015. Doctoral Dissertation, University of Southern California. Accessed February 27, 2020. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/545519/rec/1058.

MLA Handbook (7th Edition):

Alayed, Hashem Ali. “Behavior-based approaches for detecting cheating in online games.” 2015. Web. 27 Feb 2020.

Vancouver:

Alayed HA. Behavior-based approaches for detecting cheating in online games. [Internet] [Doctoral dissertation]. University of Southern California; 2015. [cited 2020 Feb 27]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/545519/rec/1058.

Council of Science Editors:

Alayed HA. Behavior-based approaches for detecting cheating in online games. [Doctoral Dissertation]. University of Southern California; 2015. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/545519/rec/1058


University of Southern California

13. Cho, Seong Ho. Block-based image steganalysis: algorithm and performance evaluation.

Degree: PhD, Electrical Engineering, 2012, University of Southern California

 Traditional image steganalysis techniques are conducted with respect to the entire image. In this work, we aim to differentiate a stego image from its cover… (more)

Subjects/Keywords: steganalysis; steganography; decision fusion; feature selection

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APA (6th Edition):

Cho, S. H. (2012). Block-based image steganalysis: algorithm and performance evaluation. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/81733/rec/1140

Chicago Manual of Style (16th Edition):

Cho, Seong Ho. “Block-based image steganalysis: algorithm and performance evaluation.” 2012. Doctoral Dissertation, University of Southern California. Accessed February 27, 2020. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/81733/rec/1140.

MLA Handbook (7th Edition):

Cho, Seong Ho. “Block-based image steganalysis: algorithm and performance evaluation.” 2012. Web. 27 Feb 2020.

Vancouver:

Cho SH. Block-based image steganalysis: algorithm and performance evaluation. [Internet] [Doctoral dissertation]. University of Southern California; 2012. [cited 2020 Feb 27]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/81733/rec/1140.

Council of Science Editors:

Cho SH. Block-based image steganalysis: algorithm and performance evaluation. [Doctoral Dissertation]. University of Southern California; 2012. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/81733/rec/1140


University of Southern California

14. Banerjee, Prithviraj. Incorporating aggregate feature statistics in structured dynamical models for human activity recognition.

Degree: PhD, Computer Science, 2014, University of Southern California

 Human action recognition in videos is a central problem of computer vision, with numerous applications in the fields of video surveillance, data mining and human… (more)

Subjects/Keywords: computer vision; machine learning; human activity recognition; activity detection; graphical models

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APA (6th Edition):

Banerjee, P. (2014). Incorporating aggregate feature statistics in structured dynamical models for human activity recognition. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/483796/rec/3438

Chicago Manual of Style (16th Edition):

Banerjee, Prithviraj. “Incorporating aggregate feature statistics in structured dynamical models for human activity recognition.” 2014. Doctoral Dissertation, University of Southern California. Accessed February 27, 2020. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/483796/rec/3438.

MLA Handbook (7th Edition):

Banerjee, Prithviraj. “Incorporating aggregate feature statistics in structured dynamical models for human activity recognition.” 2014. Web. 27 Feb 2020.

Vancouver:

Banerjee P. Incorporating aggregate feature statistics in structured dynamical models for human activity recognition. [Internet] [Doctoral dissertation]. University of Southern California; 2014. [cited 2020 Feb 27]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/483796/rec/3438.

Council of Science Editors:

Banerjee P. Incorporating aggregate feature statistics in structured dynamical models for human activity recognition. [Doctoral Dissertation]. University of Southern California; 2014. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/483796/rec/3438


University of Southern California

15. Hao, Xiaolin. Sharpening the edge of tools for microbial diversity analysis.

Degree: PhD, Computational Biology and Bioinformatics, 2012, University of Southern California

 Metagenomics studies have prospered from the rapid development of next-generation sequencing. However, microbial diversity analysis as an essential component of metagenomics is still facing three… (more)

Subjects/Keywords: bioinformatics; computational biology; metagenomics; clustering; bayesian

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APA (6th Edition):

Hao, X. (2012). Sharpening the edge of tools for microbial diversity analysis. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/120471/rec/5820

Chicago Manual of Style (16th Edition):

Hao, Xiaolin. “Sharpening the edge of tools for microbial diversity analysis.” 2012. Doctoral Dissertation, University of Southern California. Accessed February 27, 2020. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/120471/rec/5820.

MLA Handbook (7th Edition):

Hao, Xiaolin. “Sharpening the edge of tools for microbial diversity analysis.” 2012. Web. 27 Feb 2020.

Vancouver:

Hao X. Sharpening the edge of tools for microbial diversity analysis. [Internet] [Doctoral dissertation]. University of Southern California; 2012. [cited 2020 Feb 27]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/120471/rec/5820.

Council of Science Editors:

Hao X. Sharpening the edge of tools for microbial diversity analysis. [Doctoral Dissertation]. University of Southern California; 2012. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/120471/rec/5820

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