Papers
Tensor Decomposition via Simultaneous Power Iteration
Po-An Wang, Chi-Jen Lu
Batched High-dimensional Bayesian Optimization via Structural Kernel Learning
Zi Wang, Chengtao Li, Stefanie Jegelka et al.
Robust Probabilistic Modeling with Bayesian Data Reweighting
Yixin Wang, Alp Kucukelbir, David M. Blei
Efficient Distributed Learning with Sparsity
Jialei Wang, Mladen Kolar, Nathan Srebro et al.
Max-value Entropy Search for Efficient Bayesian Optimization
Zi Wang, Stefanie Jegelka
Robust Gaussian Graphical Model Estimation with Arbitrary Corruption
Lingxiao Wang, Quanquan Gu
Sketched Ridge Regression: Optimization Perspective, Statistical Perspective, and Model Averaging
Shusen Wang, Alex Gittens, Michael W. Mahoney
Capacity Releasing Diffusion for Speed and Locality
Di Wang, Kimon Fountoulakis, Monika Henzinger et al.
Optimal and Adaptive Off-policy Evaluation in Contextual Bandits
Yu-Xiang Wang, Alekh Agarwal, Miroslav Dudı́k
Fast Bayesian Intensity Estimation for the Permanental Process
Christian J. Walder, Adrian N. Bishop
On orthogonality and learning recurrent networks with long term dependencies
Eugene Vorontsov, Chiheb Trabelsi, Samuel Kadoury et al.
Learning to Generate Long-term Future via Hierarchical Prediction
Ruben Villegas, Jimei Yang, Yuliang Zou et al.
Scalable Multi-Class Gaussian Process Classification using Expectation Propagation
Carlos Villacampa-Calvo, Daniel Hernández-Lobato
FeUdal Networks for Hierarchical Reinforcement Learning
Alexander Sasha Vezhnevets, Simon Osindero, Tom Schaul et al.
Model-Independent Online Learning for Influence Maximization
Sharan Vaswani, Branislav Kveton, Zheng Wen et al.
Automatic Discovery of the Statistical Types of Variables in a Dataset
Isabel Valera, Zoubin Ghahramani
Learning Determinantal Point Processes with Moments and Cycles
John Urschel, Victor-Emmanuel Brunel, Ankur Moitra et al.
Learning Stable Stochastic Nonlinear Dynamical Systems
Jonas Umlauft, Sandra Hirche
Multilabel Classification with Group Testing and Codes
Shashanka Ubaru, Arya Mazumdar
Breaking Locality Accelerates Block Gauss-Seidel
Stephen Tu, Shivaram Venkataraman, Ashia C. Wilson et al.
Hyperplane Clustering via Dual Principal Component Pursuit
Manolis C. Tsakiris, René Vidal
Know-Evolve: Deep Temporal Reasoning for Dynamic Knowledge Graphs
Rakshit Trivedi, Hanjun Dai, Yichen Wang et al.
Magnetic Hamiltonian Monte Carlo
Nilesh Tripuraneni, Mark Rowland, Zoubin Ghahramani et al.
Diameter-Based Active Learning
Christopher Tosh, Sanjoy Dasgupta
Boosted Fitted Q-Iteration
Samuele Tosatto, Matteo Pirotta, Carlo D’Eramo et al.