Papers
Power-Law Graph Cuts
Xiangyang Zhou, Jiaxin Zhang, Brian Kulis
Scalable Nonparametric Multiway Data Analysis
Shandian Zhe, Zenglin Xu, Xinqi Chu et al.
A Simple Homotopy Algorithm for Compressive Sensing
Lijun Zhang, Tianbao Yang, Rong Jin et al.
Minimizing Nonconvex Non-Separable Functions
Yaoliang Yu, Xun Zheng, Micol Marchetti-Bowick et al.
A la Carte – Learning Fast Kernels
Zichao Yang, Andrew Wilson, Alex Smola et al.
Majorization-Minimization for Manifold Embedding
Zhirong Yang, Jaakko Peltonen, Samuel Kaski
Understanding and Evaluating Sparse Linear Discriminant Analysis
Yi Wu, David Wipf, Jeong-Min Yun
A Greedy Homotopy Method for Regression with Nonconvex Constraints
Fabian Wauthier, Peter Donnelly
Trend Filtering on Graphs
Yu-Xiang Wang, James Sharpnack, Alex Smola et al.
Column Subset Selection with Missing Data via Active Sampling
Yining Wang, Aarti Singh
Multi-Manifold Modeling in Non-Euclidean spaces
Xu Wang, Konstantinos Slavakis, Gilad Lerman
Falling Rule Lists
Fulton Wang, Cynthia Rudin
Maximally Informative Hierarchical Representations of High-Dimensional Data
Greg Ver Steeg, Aram Galstyan
Learning of Non-Parametric Control Policies with High-Dimensional State Features
Herke Van Hoof, Jan Peters, Gerhard Neumann
Particle Gibbs with Ancestor Sampling for Probabilistic Programs
Jan-Willem Meent, Hongseok Yang, Vikash Mansinghka et al.
Streaming Variational Inference for Bayesian Nonparametric Mixture Models
Alex Tank, Nicholas Foti, Emily Fox
Predicting Preference Reversals via Gaussian Process Uncertainty Aversion
Rikiya Takahashi, Tetsuro Morimura
Two-stage sampled learning theory on distributions
Zoltan Szabo, Arthur Gretton, Barnabas Poczos et al.
Inferring Block Structure of Graphical Models in Exponential Families
Siqi Sun, Hai Wang, Jinbo Xu
A Dirichlet Process Mixture Model for Spherical Data
Julian Straub, Jason Chang, Oren Freifeld et al.
Calibration of conditional composite likelihood for Bayesian inference on Gibbs random fields
Julien Stoehr, Nial Friel