| Near-optimal learning of tree-structured distributions by Chow-Liu A Bhattacharyya, S Gayen, E Price, NV Vinodchandran Proceedings of the 53rd Annual ACM SIGACT Symposium on Theory of Computing …, 2021 | 37 | 2021 |
| On Approximating Total Variation Distance A Bhattacharyya, S Gayen, KS Meel, D Myrisiotis, A Pavan, ... arXiv preprint arXiv:2206.07209, 2022 | 22 | 2022 |
| Efficient distance approximation for structured high-dimensional distributions via learning A Bhattacharyya, S Gayen, KS Meel, NV Vinodchandran Advances in Neural Information Processing Systems 33, 14699-14711, 2020 | 22 | 2020 |
| Kmerestimate: A streaming algorithm for estimating k-mer counts with optimal space usage S Behera, S Gayen, JS Deogun, NV Vinodchandran Proceedings of the 2018 ACM International Conference on Bioinformatics …, 2018 | 15 | 2018 |
| Learning and Sampling of Atomic Interventions from Observations A Bhattacharyya, S Gayen, S Kandasamy, A Maran, VN Variyam International Conference on Machine Learning, 842-853, 2020 | 12* | 2020 |
| Efficient interventional distribution learning in the PAC framework A Bhattacharyya, S Gayen, S Kandasamy, V Raval, VN Variyam International Conference on Artificial Intelligence and Statistics, 7531-7549, 2022 | 8* | 2022 |
| Testing Product Distributions: A Closer Look A Bhattacharyya, S Gayen, S Kandasamy, NV Vinodchandran Algorithmic Learning Theory, 367-396, 2021 | 7 | 2021 |
| Perfect Zero Knowledge: New Upperbounds and Relativized Separations P Dixon, S Gayen, A Pavan, NV Vinodchandran Theory of Cryptography Conference, 684-704, 2020 | 6 | 2020 |
| Learning Sparse Fixed-Structure Gaussian Bayesian Networks A Bhattacharyya, D Choo, R Gajjala, S Gayen, Y Wang International Conference on Artificial Intelligence and Statistics, 9400-9429, 2022 | 3 | 2022 |
| New algorithms for distributed sliding windows S Gayen, NV Vinodchandran 16th Scandinavian Symposium and Workshops on Algorithm Theory (SWAT 2018), 2018 | 3 | 2018 |
| Total Variation Distance Meets Probabilistic Inference A Bhattacharyya, S Gayen, KS Meel, D Myrisiotis, A Pavan, ... Forty-first International Conference on Machine Learning, 0 | 3 | |
| Algorithms for k-median Clustering over Distributed Streams S Gayen, NV Vinodchandran Computing and Combinatorics: 22nd International Conference, COCOON 2016, Ho …, 2016 | 2 | 2016 |
| Computational Explorations of Total Variation Distance A Bhattacharyya, S Gayen, KS Meel, D Myrisiotis, A Pavan, ... arXiv preprint arXiv:2412.10370, 2024 | | 2024 |
| Efficient Sample-optimal Learning of Gaussian Tree Models via Sample-optimal Testing of Gaussian Mutual Information S Gayen, S Kale, S Sen arXiv preprint arXiv:2411.11516, 2024 | | 2024 |
| Learnability of Parameter-Bounded Bayes Nets A Bhattacharyya, D Choo, S Gayen, D Myrisiotis arXiv preprint arXiv:2407.00927, 2024 | | 2024 |
| Total Variation Distance for Product Distributions is -Complete A Bhattacharyya, S Gayen, KS Meel, D Myrisiotis, A Pavan, ... arXiv preprint arXiv:2405.08255, 2024 | | 2024 |
| Distribution Learning Meets Graph Structure Sampling A Bhattacharyya, S Gayen, PG John, S Sen, NV Vinodchandran arXiv preprint arXiv:2405.07914, 2024 | | 2024 |
Vinodchandran VariyamProfessor, Computer Science and Engineering, University of Nebraska-Lincoln在 cse.unl.edu 的电子邮件经过验证