Drawing Biological Understanding From Machine Learning
Forest Yang [2024]

Implicit Learning in Deep Models: Enhancing Extrapolation Power and Sparsity
Alicia Tsai [2024]

Constrained machine learning: algorithms and models
Geoffrey Negiar [2023]

Efficient Optimization Algorithms for Machine Learning
Armin Askari [2022]

Implicit Models: Theories and Applications
Fangda Gu [2021]

Safety Methods for Robotic Systems
Chia-Yin Shih [2021]

Fast Randomized Algorithms for Convex Optimization and Statistical Estimation
Mert Pilanci [2016]

Sparse optimization models with robust sketching and applications
Vu Pham [2016]

Fast and Effective Approximations for Summarization and Categorization of Very Large Text Corpora
Andrew Godbehere [2015]

Robust Optimization and Data Approximation in Machine Learning
Gia Vinh Anh Pham [2015]

Low-Dimensional Models for PCA and Regression
Dapo Omidiran [2013]

Convex Approaches to Text Summarization
Brian Christopher Gawalt [2012]

Architectural Principles of Phosphorelay Signaling Networks
Josh Hug [2011]

Sparse Principal Component Analysis: Algorithms and Applications
Youwei Zhang [2011]

Sparse Coding Models of Natural Images: Algorithms for Efficient Inference and Learning of Higher-Order Structure
Pierre Jerome Garrigues [2009]

Model Selection Through Sparse Maximum Likelihood Estimation for Multivariate Gaussian or Binary Data
Onureena Banerjee [2007]

Convex Approximation and Optimization with Applications in Magnitude Filter Design and Radiation Pattern Synthesis
Peter William Kassakian [2006]

Learning with Multiple Kernels: Semidefinite Programming, Duality, Efficient Optimization and Applications in Computational Biology
Gert R. G. Lanckriet [2005]

Robust Markov Decision Processes with Uncertain Transition Matrices
Arnab Nilim [2004]