A Simple Unified Framework for High Dimensional Bandit Problems W Li, A Barik, J Honorio arXiv preprint arXiv:2102.09626, 2021 | 23 | 2021 |
Fair Sparse Regression with Clustering: An Invex Relaxation for a Combinatorial Problem A Barik, J Honorio arXiv preprint arXiv:2102.09704, 2021 | 8 | 2021 |
Learning Bayesian networks with low rank conditional probability tables A Barik, J Honorio arXiv preprint arXiv:1905.12552, 2019 | 8 | 2019 |
Provable computational and statistical guarantees for efficient learning of continuous-action graphical games A Barik, J Honorio arXiv preprint arXiv:1911.04225, 2019 | 7* | 2019 |
Provable Sample Complexity Guarantees for Learning of Continuous-Action Graphical Games with Nonparametric Utilities A Barik, J Honorio arXiv preprint arXiv:2004.01022, 2020 | 4 | 2020 |
Exact Support Recovery in Federated Regression with One-shot Communication A Barik, J Honorio arXiv preprint arXiv:2006.12583, 2020 | 2 | 2020 |
Information theoretic limits for linear prediction with graph-structured sparsity A Barik, J Honorio, M Tawarmalani 2017 IEEE International Symposium on Information Theory (ISIT), 2348-2352, 2017 | 2 | 2017 |
Information-Theoretic Bounds for Integral Estimation DQ Adams, A Barik, J Honorio arXiv preprint arXiv:2102.10199, 2021 | 1 | 2021 |
Information Theoretic Limits for Standard and One-Bit Compressed Sensing with Graph-Structured Sparsity A Barik, J Honorio arXiv preprint arXiv:1811.06635, 2018 | | 2018 |
Learning discrete Bayesian networks in polynomial time and sample complexity A Barik, J Honorio arXiv preprint arXiv:1803.04087, 2018 | | 2018 |