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University of California, Los Angeles. Statistics 0891. degree granting institution.

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Cover image for Algorithms and Theory for Variational Inference in Two-Level Non-conjugate Models

Algorithms and Theory for Variational Inference in Two-Level Non-conjugate Models

1.

Algorithms and Theory for Variational Inference in Two-Level Non-conjugate Models

by

Sheth, Rishit, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:13425272

Format:

Excerpt:

Algorithms and Theory for Variational Inference in Two-Level Non-conjugate Models / Sheth, Rishit

Cover image for Multiple Testing and False Discovery Rate Control: Theory, Methods and Algorithms

Multiple Testing and False Discovery Rate Control: Theory, Methods and Algorithms

2.

Multiple Testing and False Discovery Rate Control: Theory, Methods and Algorithms

by

Chen, Shiyun, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:13428625

Format:

Excerpt:

Multiple Testing and False Discovery Rate Control: Theory, Methods and Algorithms / Chen, Shiyun

Cover image for Statistics Meets Optimization: Computational Guarantees for Statistical Learning Algorithms

Statistics Meets Optimization: Computational Guarantees for Statistical Learning Algorithms

3.

Statistics Meets Optimization: Computational Guarantees for Statistical Learning Algorithms

by

Yang, Fan, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10931587

Format:

Excerpt:

Statistics Meets Optimization: Computational Guarantees for Statistical Learning Algorithms / Yang

Cover image for Performance Comparison of Imputation Algorithms on Missing at Random Data

Performance Comparison of Imputation Algorithms on Missing at Random Data

4.

Performance Comparison of Imputation Algorithms on Missing at Random Data

by

Addo, Evans Dapaa, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10904504

Format:

Excerpt:

Performance Comparison of Imputation Algorithms on Missing at Random Data / Addo, Evans Dapaa

Cover image for Non-convex Phase Retrieval Algorithms and Performance Analysis

Non-convex Phase Retrieval Algorithms and Performance Analysis

5.

Non-convex Phase Retrieval Algorithms and Performance Analysis

by

Wang, Gang, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10786396

Format:

Excerpt:

Non-convex Phase Retrieval Algorithms and Performance Analysis / Wang, Gang, author.

Cover image for Algorithms and Algorithmic Obstacles for Probabilistic Combinatorial Structures

Algorithms and Algorithmic Obstacles for Probabilistic Combinatorial Structures

6.

Algorithms and Algorithmic Obstacles for Probabilistic Combinatorial Structures

by

Li, Quan, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10902456

Format:

Excerpt:

Algorithms and Algorithmic Obstacles for Probabilistic Combinatorial Structures / Li, Quan, author.

Cover image for The mathematical theory of optimal linear regression design

The mathematical theory of optimal linear regression design

7.

The mathematical theory of optimal linear regression design

by

Tzougas, John George, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10868014

Format:

Excerpt:

function &phis; is presented with emphasis on the role of differentiability of &phis;. Algorithms are

Cover image for Essays on Random Forest Ensembles

Essays on Random Forest Ensembles

8.

Essays on Random Forest Ensembles

by

Olson, Matthew, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10786136

Format:

Excerpt:

algorithms or neural networks, admit natural interpretations as maximum likelihood, a suitable statistical

Cover image for Latent Variable Models for Understanding User Behavior in Software Applications

Latent Variable Models for Understanding User Behavior in Software Applications

9.

Latent Variable Models for Understanding User Behavior in Software Applications

by

Saeedi, Ardavan, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10902470

Format:

Excerpt:

models; I introduce models and inference algorithms for time series segmentation which are scalable to

Cover image for Optimal Latin Hypercube Designs for Computer Experiments Based on Multiple Objectives

Optimal Latin Hypercube Designs for Computer Experiments Based on Multiple Objectives

10.

Optimal Latin Hypercube Designs for Computer Experiments Based on Multiple Objectives

by

Hou, Ruizhe, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10784097

Format:

Excerpt:

develops new algorithms for constructing optimal LHDs that achieve nice properties on both criteria based

Cover image for Tensor-Related Methods in High Dimensional Statistics

Tensor-Related Methods in High Dimensional Statistics

11.

Tensor-Related Methods in High Dimensional Statistics

by

Chen, Han, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10286726

Format:

Excerpt:

compared in simulation setting. An R package named TensorRegression was built to present the algorithms

Cover image for Feature Selection and Classification for High-Dimensional Biological Data Under Cross-Validation Framework

Feature Selection and Classification for High-Dimensional Biological Data Under Cross-Validation Framework

12.

Feature Selection and Classification for High-Dimensional Biological Data Under Cross-Validation Framework

by

Zhong, Yi, author.

http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqm&rft_dat=xri:pqdiss:10817332

Format:

Excerpt:

learning algorithms to analyze high-dimensional biological datasets; (3) improved cross-validation and

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