| 2019 | Combinatorial Algorithms for Optimal Design. | Vivek Madan, Mohit Singh, Uthaipon Tantipongpipat, Weijun Xie |
| 2019 | Nearly Minimax-Optimal Regret for Linearly Parameterized Bandits. | Yingkai Li, Yining Wang, Yuan Zhou |
| 2019 | Sharp Theoretical Analysis for Nonparametric Testing under Random Projection. | Meimei Liu, Zuofeng Shang, Guang Cheng |
| 2019 | On Mean Estimation for General Norms with Statistical Queries. | Jerry Li, Aleksandar Nikolov, Ilya P. Razenshteyn, Erik Waingarten |
| 2019 | Solving Empirical Risk Minimization in the Current Matrix Multiplication Time. | Yin Tat Lee, Zhao Song, Qiuyi Zhang |
| 2019 | An Information-Theoretic Approach to Minimax Regret in Partial Monitoring. | Tor Lattimore, Csaba Szepesvri |
| 2019 | Global Convergence of the EM Algorithm for Mixtures of Two Component Linear Regression. | Jeongyeol Kwon, Wei Qian, Constantine Caramanis, Yudong Chen, Damek Davis |
| 2019 | Distribution-Dependent Analysis of Gibbs-ERM Principle. | Ilja Kuzborskij, Nicol Cesa-Bianchi, Csaba Szepesvri |
| 2019 | Contextual bandits with continuous actions: Smoothing, zooming, and adapting. | Akshay Krishnamurthy, John Langford, Aleksandrs Slivkins, Chicheng Zhang |
| 2019 | Bandit Principal Component Analysis. | Wojciech Kotlowski, Gergely Neu |
| 2019 | Discrepancy, Coresets, and Sketches in Machine Learning. | Zohar S. Karnin, Edo Liberty |
| 2019 | Non-asymptotic Analysis of Biased Stochastic Approximation Scheme. | Belhal Karimi, Blazej Miasojedow, Eric Moulines, Hoi-To Wai |
| 2019 | On Communication Complexity of Classification Problems. | Daniel Kane, Roi Livni, Shay Moran, Amir Yehudayoff |
| 2019 | Privately Learning High-Dimensional Distributions. | Gautam Kamath, Jerry Li, Vikrant Singhal, Jonathan R. Ullman |
| 2019 | Parameter-Free Online Convex Optimization with Sub-Exponential Noise. | Kwang-Sung Jun, Francesco Orabona |
| 2019 | Sample complexity of partition identification using multi-armed bandits. | Sandeep Juneja, Subhashini Krishnasamy |
| 2019 | The implicit bias of gradient descent on nonseparable data. | Ziwei Ji, Matus Telgarsky |
| 2019 | Accuracy-Memory Tradeoffs and Phase Transitions in Belief Propagation. | Vishesh Jain, Frederic Koehler, Jingbo Liu, Elchanan Mossel |
| 2019 | Sample-Optimal Low-Rank Approximation of Distance Matrices. | Piotr Indyk, Ali Vakilian, Tal Wagner, David P. Woodruff |
| 2019 | A Robust Spectral Algorithm for Overcomplete Tensor Decomposition. | Samuel B. Hopkins, Tselil Schramm, Jonathan Shi |
| 2019 | How Hard is Robust Mean Estimation? | Samuel B. Hopkins, Jerry Li |
| 2019 | Reasoning in Bayesian Opinion Exchange Networks Is PSPACE-Hard. | Jan Hazla, Ali Jadbabaie, Elchanan Mossel, M. Amin Rahimian |
| 2019 | Tight analyses for non-smooth stochastic gradient descent. | Nicholas J. A. Harvey, Christopher Liaw, Yaniv Plan, Sikander Randhawa |
| 2019 | Better Algorithms for Stochastic Bandits with Adversarial Corruptions. | Anupam Gupta, Tomer Koren, Kunal Talwar |
| 2019 | Sampling and Optimization on Convex Sets in Riemannian Manifolds of Non-Negative Curvature. | Navin Goyal, Abhishek Shetty |