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Alekh Agarwal
Alekh Agarwal
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Zitiert von
Zitiert von
Jahr
Dual averaging for distributed optimization: Convergence analysis and network scaling
JC Duchi, A Agarwal, MJ Wainwright
IEEE Transactions on Automatic control 57 (3), 592-606, 2011
13822011
A reductions approach to fair classification
A Agarwal, A Beygelzimer, M Dudík, J Langford, H Wallach
International conference on machine learning, 60-69, 2018
11642018
Distributed delayed stochastic optimization
A Agarwal, JC Duchi
Advances in neural information processing systems 24, 2011
7452011
On the theory of policy gradient methods: Optimality, approximation, and distribution shift
A Agarwal, SM Kakade, JD Lee, G Mahajan
Journal of Machine Learning Research 22 (98), 1-76, 2021
724*2021
Deep batch active learning by diverse, uncertain gradient lower bounds
JT Ash, C Zhang, A Krishnamurthy, J Langford, A Agarwal
arXiv preprint arXiv:1906.03671, 2019
6902019
Taming the monster: A fast and simple algorithm for contextual bandits
A Agarwal, D Hsu, S Kale, J Langford, L Li, R Schapire
International Conference on Machine Learning, 1638-1646, 2014
5602014
Information-theoretic lower bounds on the oracle complexity of convex optimization
A Agarwal, MJ Wainwright, P Bartlett, P Ravikumar
Advances in Neural Information Processing Systems 22, 2009
4942009
Contextual decision processes with low bellman rank are pac-learnable
N Jiang, A Krishnamurthy, A Agarwal, J Langford, RE Schapire
International Conference on Machine Learning, 1704-1713, 2017
4542017
A reliable effective terascale linear learning system
A Agarwal, O Chapelle, M Dudík, J Langford
The Journal of Machine Learning Research 15 (1), 1111-1133, 2014
4452014
Fast global convergence rates of gradient methods for high-dimensional statistical recovery
A Agarwal, S Negahban, MJ Wainwright
Advances in Neural Information Processing Systems 23, 2010
4332010
Optimal Algorithms for Online Convex Optimization with Multi-Point Bandit Feedback.
A Agarwal, O Dekel, L Xiao
Colt, 28-40, 2010
4082010
Noisy matrix decomposition via convex relaxation: Optimal rates in high dimensions
A Agarwal, S Negahban, MJ Wainwright
3082012
Fair regression: Quantitative definitions and reduction-based algorithms
A Agarwal, M Dudík, ZS Wu
International Conference on Machine Learning, 120-129, 2019
2712019
Fast convergence of regularized learning in games
V Syrgkanis, A Agarwal, H Luo, RE Schapire
Advances in Neural Information Processing Systems 28, 2015
2602015
Provably efficient rl with rich observations via latent state decoding
S Du, A Krishnamurthy, N Jiang, A Agarwal, M Dudik, J Langford
International Conference on Machine Learning, 1665-1674, 2019
2562019
Bellman-consistent pessimism for offline reinforcement learning
T Xie, CA Cheng, N Jiang, P Mineiro, A Agarwal
Advances in neural information processing systems 34, 6683-6694, 2021
2552021
Reinforcement learning: Theory and algorithms
A Agarwal, N Jiang, SM Kakade, W Sun
CS Dept., UW Seattle, Seattle, WA, USA, Tech. Rep 32, 96, 2019
2542019
Flambe: Structural complexity and representation learning of low rank mdps
A Agarwal, S Kakade, A Krishnamurthy, W Sun
Advances in neural information processing systems 33, 20095-20107, 2020
2462020
Model-based rl in contextual decision processes: Pac bounds and exponential improvements over model-free approaches
W Sun, N Jiang, A Krishnamurthy, A Agarwal, J Langford
Conference on learning theory, 2898-2933, 2019
2372019
Learning to search better than your teacher
KW Chang, A Krishnamurthy, A Agarwal, H Daumé III, J Langford
International Conference on Machine Learning, 2058-2066, 2015
2232015
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