In Summer 2019, I visited Princeton University and worked with Sanjeev Arora on deep learning theory. PDF We will be updating the book this fall. Ruosong Wang*, Simon S. Du*, Lin F. Yang*, Sham M. Kakade Conference on Neural Information Processing Systems (NeurIPS) 2020 Show this thread. Contact: Please email us at bookrltheory [at] gmail [dot] com with any typos or errors you find. Come and join this fantastic annual event at Northwestern CS, specially if you are keen to watch super-polished talks by a line up of brilliant juniors in TCS: theory.cs.northwestern.edu/e … * Check out my junior co-author, Yiding Feng, who gives a talk on our recent paper on Friday! 15 Dec 2020. Predicting What You Already Know Helps: Provable Self-Supervised Learning. He co-founded the Algorithmic Foundations of Data Science Institute. In the Proceedings of the 36th International Conference on Machine Learning (ICML), 2019. Naman Agarwal, Brian Bullins, Xinyi Chen, Elad Hazan, Karan Singh, Cyril Zhang and Yi Zhang. Log In. For an appropriate comparison, consider the case in which Q7r (s, a) is … Sham M. Kakade. Authors: Chelsea Finn, Aravind Rajeswaran, Sham Kakade, Sergey Levine. I did my undergraduate study in Yao Class (2013-2017), Tsinghua University, where I worked closely with Jian Li, Pingzhong Tang and Ran Duan. Amongst his contributions, with a diverse set of … Paul G. Allen School of Computer Science & Engineering and Department of Statistics, University of Washington, Zaid Harchaoui. Simon S. Du*, Wei Hu*, Sham M. Kakade*, Jason D. Lee*, Qi Lei* International Conference on Learning Representations (ICLR) 2021. Alekh Agarwal Nan Jiang Sham M. Kakade Wen Sun. In ICLR 2020 or. View Sham Kakade’s profile on LinkedIn, the world’s largest professional community. Sham Kakade is on Facebook. Sham Kakade is on Facebook. Previously, I worked with Prof. Sham Kakade as a postdoctoral researcher in the Paul G. Allen School of Computer Science and Engineering at University of Washington, Seattle prior to joining UW-Madison. 2018 . Join Facebook to connect with Sham Kakade and others you may know. Our work builds on the synergistic relationship between local model-based control, global value function … He works on the theoretical foundations of machine learning, focusing on designing provable and practically efficient algorithms. Join Facebook to connect with Sham Kakade and others you may know. Download PDF Abstract: We propose a plan online and learn offline (POLO) framework for the setting where an agent, with an internal model, needs to continually act and learn in the world. 4. Rad Niazadeh @rad_niazadeh. Sham M Kakade University of Washington Verified email at cs.washington.edu Peter Bartlett Professor, EECS and Statistics, UC Berkeley Verified email at cs.berkeley.edu Shai Shalev-Shwartz The Hebrew University Verified email at cs.huji.ac.il In COLT 2020; Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds with Jordan Ash, Chicheng Zhang, Akshay Krishnamurthy and John Langford. 33. Provably Efficient Maximum Entropy Exploration. 3 The Natural Gradient and Policy Iteration We now compare policy improvement under the natural gradient to policy iteration. Former postdoc Sham Kakade, now on the University of Washington faculty Former postdoc Ryan Porter, now at AMA Capital Former postdoc Luis Ortiz, now on the University of Michigan-Dearborn CS faculty Former summer postdoctoral visitor John Langford, now at Microsoft Research NYC Favorites. ‪University of Washington‬ - ‪Cited by 20,052‬ - ‪Machine Learning‬ - ‪Artificial Intelligence‬ - ‪Statistics‬ - ‪Optimization‬ Two distinct research paradigms have studied this question. Authors: Kendall Lowrey, Aravind Rajeswaran, Sham Kakade, Emanuel Todorov, Igor Mordatch. Meta-learning views this problem as learning a prior over model parameters that … Nassau Inn (1.6 miles from IAS) 10 Palmer Square, Princeton, NJ 08542 - 609-921-7500; Hyatt Regency (3.1 miles from IAS) 102 Carnegie Center Drive, Princeton, NJ 08540 - 609-987-1234; Marriott Residence Inn (3.7 miles from IAS) 3563 US Route 1, Princeton, NJ 08540 - 609-799-0550 Sham Kakade retweeted. ICLR 2021. Sham Kakade (University of Washington; chair), Sanjeev Arora (Princeton University), Kristen Grauman (University of Texas at Austin), Ruslan Salakhutdinov (University … Provably Correct Automatic Subdifferentiation for Qualified Programs. 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. Princeton PhD students interested in machine learning, statistics, or optimization research, please contact me; ... Simon S. Du, Wei Hu, Sham M. Kakade, Jason D. Lee, and Qi Lei. Also see course website, linked to above. Efficient Full-Matrix Adaptive Regularization. Is Long Horizon Reinforcement Learning More Difficult Than Short Horizon Reinforcement Learning? 1. To connect with Sham, sign up for Facebook today. Sham Kakade and Jason D. Lee. We appreciate it! Download PDF Abstract: A central capability of intelligent systems is the ability to continuously build upon previous experiences to speed up and enhance learning of new tasks. Moderators: Pablo Castro (Google), Joel Lehman (Uber), and Dale Schuurmans (University of Alberta) The success of deep neural networks in modeling complicated functions has recently been applied by the reinforcement learning community, resulting in algorithms that are able to learn in environments previously thought to be much too large. (Partial) Log of changes: Fall 2020: V2 will be consistently updated. In Summer 2020, I interned at Microsoft Research, New York and worked with Sham M. Kakade on reinforcement learning. Elad Hazan, Sham Kakade, Karan Singh, Abby Van Soest. I am a Research Scientist at Google AI We also thank Sham Kakade, Anna Karlin, and Marina Meila for help with organizing at University of Washington. In NeurIPS, 2018. Paul G. Allen School of Computer Science & Engineering and Department of Statistics, University of Washington A … Other. Naman Agarwal. Also see RL Theory course website. Sham has 1 job listed on their profile. View the profiles of people named Sham Kakade. Jason D. Lee, Qi Lei, Nikunj Saunshi, and Jiacheng Zhuo. with Sham Kakade, Jason Lee and Gaurav Mahajan In COLT 2020; On the Optimality of Sparse Model-Based Planning for Markov Decision Processes with Sham Kakade and Lin Yang. No info to show. Sham Machandranath Kakade is an American computer scientist.He holds the Washington Research Foundation Data Science Chair in the Paul G. Allen School of Computer Science & Engineering at the University of Washington, with a joint appointment in the Department of Statistics. About Sham Kakade. Sign Up. I graduated from the Department of Electrical Engineering, California Institute of Technology (Caltech) where I was adviced by Prof. Babak Hassibi. He works on the theoretical foundations of machine learning, focusing on designing (and implementing) statistically and computationally efficient algorithms. Email: naman33k@gmail.com . Alekh Agarwal, Nan Jiang, Sham M. Kakade Chapter 1 1.1 Markov Decision Processes In reinforcement learning, the interactions between the agent and the environment are often described by a Markov Decision Process (MDP) [Puterman, 1994], specified by: State space S. In this course we only consider finite state spaces. Sham Kakade is a Washington Research Foundation Data Science Chair, with a joint appointment in the Department of Computer Science and the Department of Statistics at the University of Washington. ArXiv Report, arXiv:1809.08530. Action space A. Sham M. Kakade's 175 research works with 8,887 citations and 6,047 reads, including: What are the Statistical Limits of Offline RL with Linear Function Approximation?
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