Artigos com autorizações de acesso público - Karthikeyan ShanmugamSaiba mais
21 artigos disponíveis publicamente
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
Autorizações: US National Science Foundation
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
Autorizações: US National Science Foundation
Model-powered conditional independence test
R Sen, AT Suresh, K Shanmugam, AG Dimakis, S Shakkottai
Advances in neural information processing systems 30, 2017
Autorizações: US National Science Foundation, US Department of Defense
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
Autorizações: US National Science Foundation, US Department of Defense
Causal Best Intervention Identification via Importance Sampling.
R Sen, K Shanmugam, AG Dimakis, S Shakkottai
CoRR, 2017
Autorizações: US National Science Foundation, US Department of Defense
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
Autorizações: US National Science Foundation, US Department of Defense
Characterization and learning of causal graphs with latent variables from soft interventions
M Kocaoglu, A Jaber, K Shanmugam, E Bareinboim
Advances in Neural Information Processing Systems 32, 2019
Autorizações: US National Science Foundation
Causal feature selection for algorithmic fairness
S Galhotra, K Shanmugam, P Sattigeri, KR Varshney
Proceedings of the 2022 International Conference on Management of Data, 276-285, 2022
Autorizações: US National Science Foundation
Contextual bandits with latent confounders: An nmf approach
R Sen, K Shanmugam, M Kocaoglu, A Dimakis, S Shakkottai
Artificial Intelligence and Statistics, 518-527, 2017
Autorizações: US National Science Foundation, US Department of Defense
Distributed estimation of graph 4-profiles
ER Elenberg, K Shanmugam, M Borokhovich, AG Dimakis
Proceedings of the 25th International Conference on World Wide Web, 483-493, 2016
Autorizações: US National Science Foundation
A unified Ruzsa-Szemerédi framework for finite-length coded caching
K Shanmugam, AG Dimakis, J Llorca, AM Tulino
2017 51st Asilomar Conference on Signals, Systems, and Computers, 631-635, 2017
Autorizações: US National Science Foundation
Infonce loss provably learns cluster-preserving representations
A Parulekar, L Collins, K Shanmugam, A Mokhtari, S Shakkottai
The Thirty Sixth Annual Conference on Learning Theory, 1914-1961, 2023
Autorizações: US National Science Foundation, US Department of Defense
Contextual bandits with stochastic experts
R Sen, K Shanmugam, S Shakkottai
International Conference on Artificial Intelligence and Statistics, 852-861, 2018
Autorizações: US National Science Foundation, US Department of Defense, US Department of …
Combinatorial black-box optimization with expert advice
H Dadkhahi, K Shanmugam, J Rios, P Das, SC Hoffman, TD Loeffler, ...
Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020
Autorizações: US Department of Energy
Finite-sample analysis of off-policy TD-learning via generalized Bellman operators
Z Chen, ST Maguluri, S Shakkottai, K Shanmugam
Advances in Neural Information Processing Systems 34, 21440-21452, 2021
Autorizações: US National Science Foundation, US Department of Defense
Size of interventional Markov equivalence classes in random DAG models
D Katz, K Shanmugam, C Squires, C Uhler
The 22nd International Conference on Artificial Intelligence and Statistics …, 2019
Autorizações: US National Science Foundation, US Department of Defense
Efficient algorithms for coded multicasting in heterogeneous caching networks
G Vettigli, M Ji, K Shanmugam, J Llorca, AM Tulino, G Caire
Entropy 21 (3), 324, 2019
Autorizações: US National Science Foundation
Hawkesian graphical event models
X Yu, K Shanmugam, D Bhattacharjya, T Gao, D Subramanian, L Xue
International Conference on Probabilistic Graphical Models, 569-580, 2020
Autorizações: US National Science Foundation
Mix and match: an optimistic tree-search approach for learning models from mixture distributions
M Faw, R Sen, K Shanmugam, C Caramanis, S Shakkottai
Advances in Neural Information Processing Systems 33, 11010-11021, 2020
Autorizações: US National Science Foundation, US Department of Defense
PAC generalization via invariant representations
AU Parulekar, K Shanmugam, S Shakkottai
International Conference on Machine Learning, 27378-27400, 2023
Autorizações: US National Science Foundation, US Department of Defense
As informações de publicação e financiamento são determinadas automaticamente por um programa de computador