| 2019 | A recurrent Markov state-space generative model for sequences. | Anand Ramachandran, Steven S. Lumetta, Eric W. Klee, Deming Chen |
| 2019 | Connecting Weighted Automata and Recurrent Neural Networks through Spectral Learning. | Guillaume Rabusseau, Tianyu Li, Doina Precup |
| 2019 | Exponential Weights on the Hypercube in Polynomial Time. | Sudeep Raja Putta, Abhishek Shetty |
| 2019 | Classifying Signals on Irregular Domains via Convolutional Cluster Pooling. | Angelo Porrello, Davide Abati, Simone Calderara, Rita Cucchiara |
| 2019 | Support Localization and the Fisher Metric for off-the-grid Sparse Regularization. | Clarice Poon, Nicolas Keriven, Gabriel Peyr |
| 2019 | Overcomplete Independent Component Analysis via SDP. | Anastasia Podosinnikova, Amelia Perry, Alexander S. Wein, Francis R. Bach, Alexandre d'Aspremont, David A. Sontag |
| 2019 | Inferring Multidimensional Rates of Aging from Cross-Sectional Data. | Emma Pierson, Pang Wei Koh, Tatsunori B. Hashimoto, Daphne Koller, Jure Leskovec, Nick Eriksson, Percy Liang |
| 2019 | Finding the bandit in a graph: Sequential search-and-stop. | Pierre Perrault, Vianney Perchet, Michal Valko |
| 2019 | Proximal Splitting Meets Variance Reduction. | Fabian Pedregosa, Kilian Fatras, Mattia Casotto |
| 2019 | MaxHedge: Maximizing a Maximum Online. | Stephen Pasteris, Fabio Vitale, Kevin S. Chan, Shiqiang Wang, Mark Herbster |
| 2019 | Identifiability of Generalized Hypergeometric Distribution (GHD) Directed Acyclic Graphical Models. | Gunwoong Park, Hyewon Park |
| 2019 | Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows. | George Papamakarios, David C. Sterratt, Iain Murray |
| 2019 | Sparse Multivariate Bernoulli Processes in High Dimensions. | Parthe Pandit, Mojtaba Sahraee-Ardakan, Arash A. Amini, Sundeep Rangan, Alyson K. Fletcher |
| 2019 | Deep Topic Models for Multi-label Learning. | Rajat Panda, Ankit Pensia, Nikhil Mehta, Mingyuan Zhou, Piyush Rai |
| 2019 | Variational Information Planning for Sequential Decision Making. | Jason Pacheco, John W. Fisher III |
| 2019 | Variable selection for Gaussian processes via sensitivity analysis of the posterior predictive distribution. | Topi Paananen, Juho Piironen, Michael Riis Andersen, Aki Vehtari |
| 2019 | Bayesian optimisation under uncertain inputs. | Rafael Oliveira, Lionel Ott, Fabio Ramos |
| 2019 | Robust Graph Embedding with Noisy Link Weights. | Akifumi Okuno, Hidetoshi Shimodaira |
| 2019 | Graph Embedding with Shifted Inner Product Similarity and Its Improved Approximation Capability. | Akifumi Okuno, Geewook Kim, Hidetoshi Shimodaira |
| 2019 | Iterative Bayesian Learning for Crowdsourced Regression. | Jungseul Ok, Sewoong Oh, Yunhun Jang, Jinwoo Shin, Yung Yi |
| 2019 | Training a Spiking Neural Network with Equilibrium Propagation. | Peter O'Connor, Efstratios Gavves, Max Welling |
| 2019 | Sharp Analysis of Learning with Discrete Losses. | Alex Nowak-Vila, Francis R. Bach, Alessandro Rudi |
| 2019 | Stochastic Gradient Descent with Exponential Convergence Rates of Expected Classification Errors. | Atsushi Nitanda, Taiji Suzuki |
| 2019 | Learning Tree Structures from Noisy Data. | Konstantinos E. Nikolakakis, Dionysios S. Kalogerias, Anand D. Sarwate |
| 2019 | On the Dynamics of Gradient Descent for Autoencoders. | Thanh Van Nguyen, Raymond K. W. Wong, Chinmay Hegde |