Papers
Online Learning: Sufficient Statistics and the Burkholder Method
Dylan J. Foster, Alexander Rakhlin, Karthik Sridharan
The Many Faces of Exponential Weights in Online Learning
Dirk Hoeven, Tim Erven, Wojciech Kotłowski
Unleashing Linear Optimizers for Group-Fair Learning and Optimization
Daniel Alabi, Nicole Immorlica, Adam Kalai
Breaking the 1/√n Barrier: Faster Rates for Permutation-based Models in Polynomial Time
Cheng Mao, Ashwin Pananjady, Martin J. Wainwright
Approximate Nearest Neighbors in Limited Space
Piotr Indyk, Tal Wagner
Counting Motifs with Graph Sampling
Jason M. Klusowski, Yihong Wu
Hidden Integrality of SDP Relaxations for Sub-Gaussian Mixture Models
Yingjie Fei, Yudong Chen
Learning Single-Index Models in Gaussian Space
Rishabh Dudeja, Daniel Hsu
Marginal Singularity, and the Benefits of Labels in Covariate-Shift
Samory Kpotufe, Guillaume Martinet
Efficient active learning of sparse halfspaces
Chicheng Zhang
Subpolynomial trace reconstruction for random strings \{and arbitrary deletion probability
Nina Holden, Robin Pemantle, Yuval Peres
Langevin Monte Carlo and JKO splitting
Espen Bernton
Efficient Contextual Bandits in Non-stationary Worlds
Haipeng Luo, Chen-Yu Wei, Alekh Agarwal et al.
The Externalities of Exploration and How Data Diversity Helps Exploitation
Manish Raghavan, Aleksandrs Slivkins, Jennifer Vaughan Wortman et al.
An Estimate Sequence for Geodesically Convex Optimization
Hongyi Zhang, Suvrit Sra
Privacy-preserving Prediction
Cynthia Dwork, Vitaly Feldman
A Finite Time Analysis of Temporal Difference Learning With Linear Function Approximation
Jalaj Bhandari, Daniel Russo, Raghav Singal
Optimal Single Sample Tests for Structured versus Unstructured Network Data
Guy Bresler, Dheeraj Nagaraj
ℓ_1 Regression using Lewis Weights Preconditioning and Stochastic Gradient Descent
David Durfee, Kevin A. Lai, Saurabh Sawlani
Faster Rates for Convex-Concave Games
Jacob Abernethy, Kevin A. Lai, Kfir Y. Levy et al.
Smoothed Online Convex Optimization in High Dimensions via Online Balanced Descent
Niangjun Chen, Gautam Goel, Adam Wierman
Online learning over a finite action set with limited switching
Jason Altschuler, Kunal Talwar
A Direct Sum Result for the Information Complexity of Learning
Ido Nachum, Jonathan Shafer, Amir Yehudayoff