Reinforcement Learning: Theory and Algorithms

2021-11-11 · Reinforcement Learning: Theory and Algorithms Alekh Agarwal Nan Jiang Sham M. Kakade Wen Sun November 11, 2021 WORKING DRAFT: We will be frequently updating the book this fall, 2021.

Sham Machandranath Kakade: Publications

Preprints . The Benefits of Implicit Regularization from SGD in Least Squares Problems. Difan Zou, Jingfeng Wu, Vladimir Braverman, Quanquan Gu, Dean P. Foster, Sham M. Kakade

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Stat 928: Statistical Learning Theory, Spring 2011

Syllabus: Statistical learning theory studies the statistical aspects of machine learning and automated reasoning, through the use of (sampled) data. In particular, the focus is on characterizing the generalization ability of learning algorithms in terms of how well they perform on ``new'''' data when trained on some given data set.

[2103.12690] An Exponential Lower Bound for Linearly ...

2021-3-24 · An Exponential Lower Bound for Linearly-Realizable MDPs with Constant Suboptimality Gap. Authors: Yuanhao Wang, Ruosong Wang, Sham M. Kakade. Download PDF. Abstract: A fundamental question in the theory of reinforcement learning is: suppose the optimal -function lies in the linear span of a given dimensional feature mapping, is sample-efficient ...

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[1703.00887] How to Escape Saddle Points Efficiently

2017-3-3 · This paper shows that a perturbed form of gradient descent converges to a second-order stationary point in a number iterations which depends only poly-logarithmically on dimension (i.e., it is almost "dimension-free"). The convergence rate of this procedure matches the well-known convergence rate of gradient descent to first-order stationary points, up to log factors. …

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Sham M. Kakade | Paul G. Allen School of Computer …

Sham Kakade is a Washington Research Foundation Data Science Chair, with a joint appointment in both the Allen School and Department of Statistics at the University of Washington. He works on the theoretical foundations of machine learning, focusing on designing (and implementing) statistically and computationally efficient algorithms.

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2019-8-23 · ,,。 Kakade, Sham, and John Langford. "Approximately optimal approximate reinforcement learning." ICML. Vol. 2. 2002.…

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2021-1-21 · Kakademix, 。 6 3. Kakademix policy update,

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Tensor decompositions for learning latent variable models. A Anandkumar, R Ge, D Hsu, SM Kakade, M Telgarsky. Journal of machine learning research 15, 2773-2832., 2014. 1048. 2014. A natural policy gradient. S Kakade. Advances in neural information processing systems 14, …

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2021-6-8 ·  07-17 1894 Python py charm pi p py charm #enc od ing=utf-8 im po rt jieba jiebaTxt = jieba.cut('''', cut_all=Fal se ) print ''|''.join(jiebaTxt) jiebaTxt = jieba.cut('', …

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Sushrut Kakade

View Sushrut Kakade''s profile on LinkedIn, the world''s largest professional community. Sushrut has 1 job listed on their profile. See the complete profile on …

Bhagwan Kakade

View Bhagwan Kakade''s profile on LinkedIn, the world''s largest professional community. Bhagwan has 1 job listed on their profile. See the complete profile …

tejaswinikakade (tejaswini kakade) · GitHub

Be Creative. Sky is Not The Limit. tejaswinikakade has 25 repositories available. Follow their code on GitHub.

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