Articoli con mandati relativi all'accesso pubblico - Sujay SanghaviUlteriori informazioni
Non disponibili pubblicamente: 2
Structured low-rank matrix factorization for haplotype assembly
C Cai, S Sanghavi, H Vikalo
IEEE Journal of Selected Topics in Signal Processing 10 (4), 647-657, 2016
Mandati: US National Science Foundation
Structurally-constrained gradient descent for matrix factorization in haplotype assembly problems
C Cai, S Sanghavi, H Vikalo
2016 IEEE International Conference on Acoustics, Speech and Signal …, 2016
Mandati: US National Science Foundation
Disponibili pubblicamente: 26
Learning with bad training data via iterative trimmed loss minimization
Y Shen, S Sanghavi
International conference on machine learning, 5739-5748, 2019
Mandati: US National Science Foundation
Faster non-convex federated learning via global and local momentum
R Das, A Acharya, A Hashemi, S Sanghavi, IS Dhillon, U Topcu
Uncertainty in Artificial Intelligence, 496-506, 2022
Mandati: US National Science Foundation, US Department of Defense, US National …
Sparse logistic regression learns all discrete pairwise graphical models
S Wu, S Sanghavi, AG Dimakis
Advances in Neural Information Processing Systems 32, 2019
Mandati: US National Science Foundation
Learning a compressed sensing measurement matrix via gradient unrolling
S Wu, A Dimakis, S Sanghavi, F Yu, D Holtmann-Rice, D Storcheus, ...
International Conference on Machine Learning, 6828-6839, 2019
Mandati: US National Science Foundation, US Department of Defense
Nearly horizon-free offline reinforcement learning
T Ren, J Li, B Dai, SS Du, S Sanghavi
Advances in neural information processing systems 34, 15621-15634, 2021
Mandati: US National Science Foundation
Blocking bandits
S Basu, R Sen, S Sanghavi, S Shakkottai
Advances in Neural Information Processing Systems 32, 2019
Mandati: US National Science Foundation, US Department of Defense
On the benefits of multiple gossip steps in communication-constrained decentralized federated learning
A Hashemi, A Acharya, R Das, H Vikalo, S Sanghavi, I Dhillon
IEEE Transactions on Parallel and Distributed Systems 33 (11), 2727-2739, 2021
Mandati: US National Science Foundation
Provable compressed sensing quantum state tomography via non-convex methods
A Kyrillidis, A Kalev, D Park, S Bhojanapalli, C Caramanis, S Sanghavi
npj Quantum Information 4 (1), 36, 2018
Mandati: US Department of Defense
Robust training in high dimensions via block coordinate geometric median descent
A Acharya, A Hashemi, P Jain, S Sanghavi, IS Dhillon, U Topcu
International Conference on Artificial Intelligence and Statistics, 11145-11168, 2022
Mandati: US National Science Foundation, US Department of Defense
Iterative least trimmed squares for mixed linear regression
Y Shen, S Sanghavi
Advances in Neural Information Processing Systems 32, 2019
Mandati: US National Science Foundation
Matrix completion with column manipulation: Near-optimal sample-robustness-rank tradeoffs
Y Chen, H Xu, C Caramanis, S Sanghavi
IEEE Transactions on Information Theory 62 (1), 503-526, 2015
Mandati: A*Star, Singapore
Learning distributions generated by one-layer ReLU networks
S Wu, AG Dimakis, S Sanghavi
Advances in neural information processing systems 32, 2019
Mandati: US National Science Foundation
Sample efficiency of data augmentation consistency regularization
S Yang, Y Dong, R Ward, IS Dhillon, S Sanghavi, Q Lei
International Conference on Artificial Intelligence and Statistics, 3825-3853, 2023
Mandati: US National Science Foundation, US Department of Defense
Online collaborative filtering on graphs
S Banerjee, S Sanghavi, S Shakkottai
Operations Research 64 (3), 756-769, 2016
Mandati: US National Science Foundation, US Department of Transportation
Minimax regret for cascading bandits
D Vial, S Sanghavi, S Shakkottai, R Srikant
Advances in Neural Information Processing Systems 35, 29126-29138, 2022
Mandati: US National Science Foundation, US Department of Defense
Linear bandit algorithms with sublinear time complexity
S Yang, T Ren, S Shakkottai, E Price, IS Dhillon, S Sanghavi
International Conference on Machine Learning, 25241-25260, 2022
Mandati: US National Science Foundation
Understanding self-distillation in the presence of label noise
R Das, S Sanghavi
International Conference on Machine Learning, 7102-7140, 2023
Mandati: US National Science Foundation
Towards statistical and computational complexities of Polyak step size gradient descent
T Ren, F Cui, A Atsidakou, S Sanghavi, N Ho
International Conference on Artificial Intelligence and Statistics, 3930-3961, 2022
Mandati: US National Science Foundation
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