| 2020 | Ordered SGD: A New Stochastic Optimization Framework for Empirical Risk Minimization. | Kenji Kawaguchi, Haihao Lu |
| 2020 | Elimination of All Bad Local Minima in Deep Learning. | Kenji Kawaguchi, Leslie Pack Kaelbling |
| 2020 | The True Sample Complexity of Identifying Good Arms. | Julian Katz-Samuels, Kevin Jamieson |
| 2020 | Model-Agnostic Counterfactual Explanations for Consequential Decisions. | Amir-Hossein Karimi, Gilles Barthe, Borja Balle, Isabel Valera |
| 2020 | Optimal Deterministic Coresets for Ridge Regression. | Praneeth Kacham, David P. Woodruff |
| 2020 | Graph Coarsening with Preserved Spectral Properties. | Yu Jin, Andreas Loukas, Joseph F. JJ |
| 2020 | Inference of Dynamic Graph Changes for Functional Connectome. | Dingjue Ji, Junwei Lu, Yiliang Zhang, Siyuan Gao, Hongyu Zhao |
| 2020 | Identifying and Correcting Label Bias in Machine Learning. | Heinrich Jiang, Ofir Nachum |
| 2020 | Feature relevance quantification in explainable AI: A causal problem. | Dominik Janzing, Lenon Minorics, Patrick Blbaum |
| 2020 | Bandit optimisation of functions in the Matrn kernel RKHS. | David Janz, David R. Burt, Javier Gonzlez |
| 2020 | Spatio-temporal alignments: Optimal transport through space and time. | Hicham Janati, Marco Cuturi, Alexandre Gramfort |
| 2020 | Efficient Distributed Hessian Free Algorithm for Large-scale Empirical Risk Minimization via Accumulating Sample Strategy. | Majid Jahani, Xi He, Chenxin Ma, Aryan Mokhtari, Dheevatsa Mudigere, Alejandro Ribeiro, Martin Takc |
| 2020 | Flexible distribution-free conditional predictive bands using density estimators. | Rafael Izbicki, Gilson Y. Shimizu, Rafael Bassi Stern |
| 2020 | An Optimal Algorithm for Bandit Convex Optimization with Strongly-Convex and Smooth Loss. | Shinji Ito |
| 2020 | Stopping criterion for active learning based on deterministic generalization bounds. | Hideaki Ishibashi, Hideitsu Hino |
| 2020 | Fast Noise Removal for k-Means Clustering. | Sungjin Im, Mahshid Montazer Qaem, Benjamin Moseley, Xiaorui Sun, Rudy Zhou |
| 2020 | Optimal sampling in unbiased active learning. | Henrik Imberg, Johan Jonasson, Marina Axelson-Fisk |
| 2020 | A Theoretical and Practical Framework for Regression and Classification from Truncated Samples. | Andrew Ilyas, Emmanouil Zampetakis, Constantinos Daskalakis |
| 2020 | Robust Optimisation Monte Carlo. | Borislav Ikonomov, Michael U. Gutmann |
| 2020 | Local Differential Privacy for Sampling. | Hisham Husain, Borja Balle, Zac Cranko, Richard Nock |
| 2020 | Uncertainty Quantification for Deep Context-Aware Mobile Activity Recognition and Unknown Context Discovery. | Zepeng Huo, Arash Pakbin, Xiaohan Chen, Nathan C. Hurley, Ye Yuan, Xiaoning Qian, Zhangyang Wang, Shuai Huang, Bobak Mortazavi |
| 2020 | Fast Markov chain Monte Carlo algorithms via Lie groups. | Steve Huntsman |
| 2020 | Sharp Thresholds of the Information Cascade Fragility Under a Mismatched Model. | Wasim Huleihel, Ofer Shayevitz |
| 2020 | Validated Variational Inference via Practical Posterior Error Bounds. | Jonathan H. Huggins, Mikolaj J. Kasprzak, Trevor Campbell, Tamara Broderick |
| 2020 | Stochastic Neural Network with Kronecker Flow. | Chin-Wei Huang, Ahmed Touati, Pascal Vincent, Gintare Karolina Dziugaite, Alexandre Lacoste, Aaron C. Courville |