| 2019 | Sample Efficient Graph-Based Optimization with Noisy Observations. | Thanh Tan Nguyen, Ali Shameli, Yasin Abbasi-Yadkori, Anup Rao, Branislav Kveton |
| 2019 | Gaussian Regression with Convex Constraints. | Matey Neykov |
| 2019 | Tossing Coins Under Monotonicity. | Matey Neykov |
| 2019 | Learning Natural Programs from a Few Examples in Real-Time. | Nagarajan Natarajan, Danny Simmons, Naren Datha, Prateek Jain, Sumit Gulwani |
| 2019 | Inverting Supervised Representations with Autoregressive Neural Density Models. | Charlie Nash, Nate Kushman, Christopher K. I. Williams |
| 2019 | Stochastic Gradient Descent on Separable Data: Exact Convergence with a Fixed Learning Rate. | Mor Shpigel Nacson, Nathan Srebro, Daniel Soudry |
| 2019 | Convergence of Gradient Descent on Separable Data. | Mor Shpigel Nacson, Jason D. Lee, Suriya Gunasekar, Pedro Henrique Pamplona Savarese, Nathan Srebro, Daniel Soudry |
| 2019 | Best of many worlds: Robust model selection for online supervised learning. | Vidya Muthukumar, Mitas Ray, Anant Sahai, Peter L. Bartlett |
| 2019 | Gain estimation of linear dynamical systems using Thompson Sampling. | Matias I. Mller, Cristian R. Rojas |
| 2019 | Globally-convergent Iteratively Reweighted Least Squares for Robust Regression Problems. | Bhaskar Mukhoty, Govind Gopakumar, Prateek Jain, Purushottam Kar |
| 2019 | Reducing training time by efficient localized kernel regression. | Nicole Mcke |
| 2019 | Sobolev Descent. | Youssef Mroueh, Tom Sercu, Anant Raj |
| 2019 | On the Connection Between Learning Two-Layer Neural Networks and Tensor Decomposition. | Marco Mondelli, Andrea Montanari |
| 2019 | Doubly Semi-Implicit Variational Inference. | Dmitry Molchanov, Valery Kharitonov, Artem Sobolev, Dmitry P. Vetrov |
| 2019 | Efficient Nonconvex Empirical Risk Minimization via Adaptive Sample Size Methods. | Aryan Mokhtari, Asuman E. Ozdaglar, Ali Jadbabaie |
| 2019 | Adaptive Minimax Regret against Smooth Logarithmic Losses over High-Dimensional l1-Balls via Envelope Complexity. | Kohei Miyaguchi, Kenji Yamanishi |
| 2019 | Domain-Size Aware Markov Logic Networks. | Happy Mittal, Ayush Bhardwaj, Vibhav Gogate, Parag Singla |
| 2019 | Unbiased Smoothing using Particle Independent Metropolis-Hastings. | Lawrece Middleton, George Deligiannidis, Arnaud Doucet, Pierre E. Jacob |
| 2019 | Imitation-Regularized Offline Learning. | Yifei Ma, Yu-Xiang Wang, Balakrishnan Narayanaswamy |
| 2019 | Estimation of Non-Normalized Mixture Models. | Takeru Matsuda, Aapo Hyvrinen |
| 2019 | Testing Conditional Independence on Discrete Data using Stochastic Complexity. | Alexander Marx, Jilles Vreeken |
| 2019 | Augmented Ensemble MCMC sampling in Factorial Hidden Markov Models. | Kaspar Mrtens, Michalis K. Titsias, Christopher Yau |
| 2019 | Estimating Network Structure from Incomplete Event Data. | Benjamin Mark, Garvesh Raskutti, Rebecca Willett |
| 2019 | Foundations of Sequence-to-Sequence Modeling for Time Series. | Zelda Mariet, Vitaly Kuznetsov |
| 2019 | Learning Determinantal Point Processes by Corrective Negative Sampling. | Zelda Mariet, Mike Gartrell, Suvrit Sra |