Papers
Robust Vertex Enumeration for Convex Hulls in High Dimensions
Pranjal Awasthi, Bahman Kalantari, Yikai Zhang
Communication-Avoiding Optimization Methods for Distributed Massive-Scale Sparse Inverse Covariance Estimation
Penporn Koanantakool, Alnur Ali, Ariful Azad et al.
Teacher Improves Learning by Selecting a Training Subset
Yuzhe Ma, Robert Nowak, Philippe Rigollet et al.
Stochastic Zeroth-order Optimization in High Dimensions
Yining Wang, Simon Du, Sivaraman Balakrishnan et al.
Linear Stochastic Approximation: How Far Does Constant Step-Size and Iterate Averaging Go?
Chandrashekar Lakshminarayanan, Csaba Szepesvari
Kernel Conditional Exponential Family
Michael Arbel, Arthur Gretton
Minimax Reconstruction Risk of Convolutional Sparse Dictionary Learning
Shashank Singh, Barnabas Poczos, Jian Ma
Cheap Checking for Cloud Computing: Statistical Analysis via Annotated Data Streams
Chris Hickey, Graham Cormode
Multimodal Prediction and Personalization of Photo Edits with Deep Generative Models
Ardavan Saeedi, Matthew Hoffman, Stephen DiVerdi et al.
Sketching for Kronecker Product Regression and P-splines
Huaian Diao, Zhao Song, Wen Sun et al.
Nested CRP with Hawkes-Gaussian Processes
Xi Tan, Vinayak Rao, Jennifer Neville
Robustness of classifiers to uniform ℓ_p and Gaussian noise
Jean-Yves Franceschi, Alhussein Fawzi, Omar Fawzi
Sparse Linear Isotonic Models
Sheng Chen, Arindam Banerjee
Why Adaptively Collected Data Have Negative Bias and How to Correct for It
Xinkun Nie, Xiaoying Tian, Jonathan Taylor et al.
Multiphase MCMC Sampling for Parameter Inference in Nonlinear Ordinary Differential Equations
Alan Lazarus, Dirk Husmeier, Theodore Papamarkou
Policy Evaluation and Optimization with Continuous Treatments
Nathan Kallus, Angela Zhou
A Generic Approach for Escaping Saddle points
Sashank Reddi, Manzil Zaheer, Suvrit Sra et al.
Structured Factored Inference for Probabilistic Programming
Avi Pfeffer, Brian Ruttenberg, William Kretschmer et al.
VAE with a VampPrior
Jakub Tomczak, Max Welling
Adaptive balancing of gradient and update computation times using global geometry and approximate subproblems
Sai Praneeth Reddy Karimireddy, Sebastian Stich, Martin Jaggi
Differentially Private Regression with Gaussian Processes
Michael T. Smith, Mauricio A. Álvarez, Max Zwiessele et al.
Provable Estimation of the Number of Blocks in Block Models
Bowei Yan, Purnamrita Sarkar, Xiuyuan Cheng
Submodularity on Hypergraphs: From Sets to Sequences
Marko Mitrovic, Moran Feldman, Andreas Krause et al.
Bayesian Approaches to Distribution Regression
Ho Chung Leon Law, Danica J. Sutherland, Dino Sejdinovic et al.
Optimality of Approximate Inference Algorithms on Stable Instances
Hunter Lang, David Sontag, Aravindan Vijayaraghavan