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Adam Block
Adam Block
PhD Student, MIT
Verified email at mit.edu - Homepage
Title
Cited by
Cited by
Year
Generative modeling with denoising auto-encoders and Langevin sampling
A Block, Y Mroueh, A Rakhlin
arXiv preprint arXiv:2002.00107, 2020
652020
Smoothed online learning is as easy as statistical learning
A Block, Y Dagan, N Golowich, A Rakhlin
Conference on Learning Theory, 1716-1786, 2022
332022
Intrinsic dimension estimation using Wasserstein distance
A Block, Z Jia, Y Polyanskiy, A Rakhlin
Journal of Machine Learning Research 23 (313), 1-37, 2022
20*2022
Majorizing measures, sequential complexities, and online learning
A Block, Y Dagan, A Rakhlin
Conference on Learning Theory, 587-590, 2021
172021
Fast mixing of multi-scale langevin dynamics under the manifold hypothesis
A Block, Y Mroueh, A Rakhlin, J Ross
arXiv preprint arXiv:2006.11166, 2020
172020
Smoothed online learning for prediction in piecewise affine systems
A Block, M Simchowitz, R Tedrake
Advances in Neural Information Processing Systems 36, 2024
92024
Efficient and near-optimal smoothed online learning for generalized linear functions
A Block, M Simchowitz
Advances in neural information processing systems 35, 7477-7489, 2022
92022
Provable guarantees for generative behavior cloning: Bridging low-level stability and high-level behavior
A Block, A Jadbabaie, D Pfrommer, M Simchowitz, R Tedrake
Advances in Neural Information Processing Systems 36, 2024
6*2024
Efficient model-free exploration in low-rank mdps
Z Mhammedi, A Block, DJ Foster, A Rakhlin
Advances in Neural Information Processing Systems 36, 2024
62024
The sample complexity of approximate rejection sampling with applications to smoothed online learning
A Block, Y Polyanskiy
The Thirty Sixth Annual Conference on Learning Theory, 228-273, 2023
62023
Oracle-efficient smoothed online learning for piecewise continuous decision making
A Block, M Simchowitz, A Rakhlin
The Thirty Sixth Annual Conference on Learning Theory, 1618-1665, 2023
52023
Rate of convergence of the smoothed empirical Wasserstein distance
A Block, Z Jia, Y Polyanskiy, A Rakhlin
arXiv preprint arXiv:2205.02128, 2022
52022
Counterfactual learning to rank for utility-maximizing query autocompletion
A Block, R Kidambi, DN Hill, T Joachims, IS Dhillon
Proceedings of the 45th International ACM SIGIR Conference on Research and …, 2022
42022
Butterfly effects of sgd noise: Error amplification in behavior cloning and autoregression
A Block, DJ Foster, A Krishnamurthy, M Simchowitz, C Zhang
arXiv preprint arXiv:2310.11428, 2023
12023
On the Performance of Empirical Risk Minimization with Smoothed Data
A Block, A Rakhlin, A Shetty
arXiv preprint arXiv:2402.14987, 2024
2024
Oracle-Efficient Differentially Private Learning with Public Data
A Block, M Bun, R Desai, A Shetty, S Wu
arXiv preprint arXiv:2402.09483, 2024
2024
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Articles 1–16