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

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

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

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

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

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

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

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

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

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

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

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