| Femtocaching: Wireless content delivery through distributed caching helpers K Shanmugam, N Golrezaei, AG Dimakis, AF Molisch, G Caire IEEE Transactions on Information Theory 59 (12), 8402-8413, 2013 | 2269 | 2013 |
| Explanations based on the missing: Towards contrastive explanations with pertinent negatives A Dhurandhar, PY Chen, R Luss, CC Tu, P Ting, K Shanmugam, P Das Advances in neural information processing systems 31, 2018 | 766 | 2018 |
| One explanation does not fit all: A toolkit and taxonomy of ai explainability techniques V Arya, RKE Bellamy, PY Chen, A Dhurandhar, M Hind, SC Hoffman, ... arXiv preprint arXiv:1909.03012, 2019 | 677* | 2019 |
| Invariant risk minimization games K Ahuja, K Shanmugam, K Varshney, A Dhurandhar International Conference on Machine Learning, 145-155, 2020 | 294 | 2020 |
| Finite-length analysis of caching-aided coded multicasting K Shanmugam, M Ji, AM Tulino, J Llorca, AG Dimakis IEEE Transactions on Information Theory 62 (10), 5524-5537, 2016 | 208 | 2016 |
| Coded caching with linear subpacketization is possible using Ruzsa-Szeméredi graphs K Shanmugam, AM Tulino, AG Dimakis 2017 IEEE International Symposium on Information Theory (ISIT), 1237-1241, 2017 | 131 | 2017 |
| Learning causal graphs with small interventions K Shanmugam, M Kocaoglu, AG Dimakis, S Vishwanath Advances in Neural Information Processing Systems 28, 2015 | 114 | 2015 |
| Causal discovery from soft interventions with unknown targets: Characterization and learning A Jaber, M Kocaoglu, K Shanmugam, E Bareinboim Advances in neural information processing systems 33, 9551-9561, 2020 | 112 | 2020 |
| Local graph coloring and index coding K Shanmugam, AG Dimakis, M Langberg 2013 IEEE International Symposium on Information Theory, 1152-1156, 2013 | 112 | 2013 |
| Model-powered conditional independence test R Sen, AT Suresh, K Shanmugam, AG Dimakis, S Shakkottai Advances in neural information processing systems 30, 2017 | 107 | 2017 |
| Leveraging latent features for local explanations R Luss, PY Chen, A Dhurandhar, P Sattigeri, Y Zhang, K Shanmugam, ... Proceedings of the 27th ACM SIGKDD conference on knowledge discovery & data …, 2021 | 96* | 2021 |
| Experimental design for learning causal graphs with latent variables M Kocaoglu, K Shanmugam, E Bareinboim Advances in Neural Information Processing Systems 30, 2017 | 96 | 2017 |
| Finite-sample analysis of contractive stochastic approximation using smooth convex envelopes Z Chen, ST Maguluri, S Shakkottai, K Shanmugam Advances in Neural Information Processing Systems 33, 8223-8234, 2020 | 92* | 2020 |
| Empirical or invariant risk minimization? a sample complexity perspective K Ahuja, J Wang, A Dhurandhar, K Shanmugam, KR Varshney arXiv preprint arXiv:2010.16412, 2020 | 91 | 2020 |
| Model agnostic contrastive explanations for structured data A Dhurandhar, T Pedapati, A Balakrishnan, PY Chen, K Shanmugam, ... arXiv preprint arXiv:1906.00117, 2019 | 90 | 2019 |
| Causal Best Intervention Identification via Importance Sampling. R Sen, K Shanmugam, AG Dimakis, S Shakkottai CoRR, 2017 | 89* | 2017 |
| Abcd-strategy: Budgeted experimental design for targeted causal structure discovery R Agrawal, C Squires, K Yang, K Shanmugam, C Uhler The 22nd International Conference on Artificial Intelligence and Statistics …, 2019 | 81 | 2019 |
| A lyapunov theory for finite-sample guarantees of markovian stochastic approximation Z Chen, ST Maguluri, S Shakkottai, K Shanmugam Operations Research 72 (4), 1352-1367, 2024 | 76* | 2024 |
| A repair framework for scalar MDS codes K Shanmugam, DS Papailiopoulos, AG Dimakis, G Caire IEEE Journal on Selected Areas in Communications 32 (5), 998-1007, 2014 | 74 | 2014 |
| Improving simple models with confidence profiles A Dhurandhar, K Shanmugam, R Luss, PA Olsen Advances in Neural Information Processing Systems 31, 2018 | 71 | 2018 |
Amit DhurandharPrincipal Research Scientist, IBM確認したメール アドレス: us.ibm.com