Papers
Accelerated Coordinate Descent with Arbitrary Sampling and Best Rates for Minibatches
Filip Hanzely, Peter Richtarik
Accelerated Decentralized Optimization with Local Updates for Smooth and Strongly Convex Objectives
Hadrien Hendrikx, Francis Bach, Laurent Massoulie
Accelerating Imitation Learning with Predictive Models
Ching-An Cheng, Xinyan Yan, Evangelos Theodorou et al.
A Continuous-Time View of Early Stopping for Least Squares Regression
Alnur Ali, J. Zico Kolter, Ryan J. Tibshirani
Active Exploration in Markov Decision Processes
Jean Tarbouriech, Alessandro Lazaric
Active multiple matrix completion with adaptive confidence sets
Andrea Locatelli, Alexandra Carpentier, Michal Valko
Active Probabilistic Inference on Matrices for Pre-Conditioning in Stochastic Optimization
Filip Roos, Philipp Hennig
Active Ranking with Subset-wise Preferences
Aadirupa Saha, Aditya Gopalan
Adaptive Activity Monitoring with Uncertainty Quantification in Switching Gaussian Process Models
Randy Ardywibowo, Guang Zhao, Zhangyang Wang et al.
Adaptive Estimation for Approximate $k$-Nearest-Neighbor Computations
Daniel LeJeune, Reinhard Heckel, Richard Baraniuk
Adaptive Gaussian Copula ABC
Yanzhi Chen, Michael U. Gutmann
Adaptive MCMC via Combining Local Samplers
Kiárash Shaloudegi, András György
Adaptive Minimax Regret against Smooth Logarithmic Losses over High-Dimensional l1-Balls via Envelope Complexity
Kohei Miyaguchi, Kenji Yamanishi
Adaptive Rao-Blackwellisation in Gibbs Sampling for Probabilistic Graphical Models
Craig Kelly, Somdeb Sarkhel, Deepak Venugopal
Adversarial Discrete Sequence Generation without Explicit NeuralNetworks as Discriminators
Zhongliang Li, Tian Xia, Xingyu Lou et al.
Adversarial Learning of a Sampler Based on an Unnormalized Distribution
Chunyuan Li, Ke Bai, Jianqiao Li et al.
Adversarial Variational Optimization of Non-Differentiable Simulators
Gilles Louppe, Joeri Hermans, Kyle Cranmer
A Family of Exact Goodness-of-Fit Tests for High-Dimensional Discrete Distributions
Feras A. Saad, Cameron E. Freer, Nathanael L. Ackerman et al.
A Fast Sampling Algorithm for Maximum Inner Product Search
QIN DING, Hsiang-Fu Yu, Cho-Jui Hsieh
A General Framework for Multi-fidelity Bayesian Optimization with Gaussian Processes
Jialin Song, Yuxin Chen, Yisong Yue
A Geometric Perspective on the Transferability of Adversarial Directions
Zachary Charles, Harrison Rosenberg, Dimitris Papailiopoulos
A Higher-Order Kolmogorov-Smirnov Test
Veeranjaneyulu Sadhanala, Yu-Xiang Wang, Aaditya Ramdas et al.
A maximum-mean-discrepancy goodness-of-fit test for censored data
Tamara Fernandez, Arthur Gretton
A Memoization Framework for Scaling Submodular Optimization to Large Scale Problems
Rishabh Iyer, Jeffrey Bilmes