Papers
Variational Information Planning for Sequential Decision Making
Jason Pacheco, John Fisher
Variational Noise-Contrastive Estimation
Benjamin Rhodes, Michael U. Gutmann
Vine copula structure learning via Monte Carlo tree search
Bo Chang, Shenyi Pan, Harry Joe
Wasserstein regularization for sparse multi-task regression
Hicham Janati, Marco Cuturi, Alexandre Gramfort
What made you do this? Understanding black-box decisions with sufficient input subsets
Brandon Carter, Jonas Mueller, Siddhartha Jain et al.
XBART: Accelerated Bayesian Additive Regression Trees
Jingyu He, Saar Yalov, P. Richard Hahn
Accelerated Stochastic Mirror Descent: From Continuous-time Dynamics to Discrete-time Algorithms
Pan Xu, Tianhao Wang, Quanquan Gu
Accelerated Stochastic Power Iteration
Peng Xu, Bryan He, Christopher De Sa et al.
Achieving the time of 1-NN, but the accuracy of k-NN
Lirong Xue, Samory Kpotufe
Actor-Critic Fictitious Play in Simultaneous Move Multistage Games
Julien Perolat, Bilal Piot, Olivier Pietquin
AdaGeo: Adaptive Geometric Learning for Optimization and Sampling
Gabriele Abbati, Alessandra Tosi, Michael Osborne et al.
Adaptive balancing of gradient and update computation times using global geometry and approximate subproblems
Sai Praneeth Reddy Karimireddy, Sebastian Stich, Martin Jaggi
Adaptive Sampling for Coarse Ranking
Sumeet Katariya, Lalit Jain, Nandana Sengupta et al.
A Fast Algorithm for Separated Sparsity via Perturbed Lagrangians
Aleksander Madry, Slobodan Mitrovic, Ludwig Schmidt
A fully adaptive algorithm for pure exploration in linear bandits
Liyuan Xu, Junya Honda, Masashi Sugiyama
A Generic Approach for Escaping Saddle points
Sashank Reddi, Manzil Zaheer, Suvrit Sra et al.
An Analysis of Categorical Distributional Reinforcement Learning
Mark Rowland, Marc Bellemare, Will Dabney et al.
A Nonconvex Proximal Splitting Algorithm under Moreau-Yosida Regularization
Emanuel Laude, Tao Wu, Daniel Cremers
An Optimization Approach to Learning Falling Rule Lists
Chaofan Chen, Cynthia Rudin
Approximate Ranking from Pairwise Comparisons
Reinhard Heckel, Max Simchowitz, Kannan Ramchandran et al.
A Provable Algorithm for Learning Interpretable Scoring Systems
Nataliya Sokolovska, Yann Chevaleyre, Jean-Daniel Zucker
A Simple Analysis for Exp-concave Empirical Minimization with Arbitrary Convex Regularizer
Tianbao Yang, Zhe Li, Lijun Zhang
A Stochastic Differential Equation Framework for Guiding Online User Activities in Closed Loop
Yichen Wang, Evangelos Theodorou, Apurv Verma et al.
Asynchronous Doubly Stochastic Group Regularized Learning
Bin Gu, Zhouyuan Huo, Heng Huang