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. 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. Sham Kakade is on Facebook. Action space A. 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. Amongst his contributions, with a diverse set of … ICLR 2021. University of Washington - Cited by 20,052 - Machine Learning - Artificial Intelligence - Statistics - Optimization Also see RL Theory course website. Elad Hazan, Sham Kakade, Karan Singh, Abby Van Soest. 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 Join Facebook to connect with Sham Kakade and others you may know. 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 Naman Agarwal, Brian Bullins, Xinyi Chen, Elad Hazan, Karan Singh, Cyril Zhang and Yi Zhang. View Sham Kakade’s profile on LinkedIn, the world’s largest professional community. Paul G. Allen School of Computer Science & Engineering and Department of Statistics, University of Washington, Zaid Harchaoui. Join Facebook to connect with Sham Kakade and others you may know. In the Proceedings of the 36th International Conference on Machine Learning (ICML), 2019. Authors: Kendall Lowrey, Aravind Rajeswaran, Sham Kakade, Emanuel Todorov, Igor Mordatch. 1. 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. Is Long Horizon Reinforcement Learning More Difficult Than Short Horizon Reinforcement Learning? We also thank Sham Kakade, Anna Karlin, and Marina Meila for help with organizing at University of Washington. Two distinct research paradigms have studied this question. Log In. View the profiles of people named Sham Kakade. Also see course website, linked to above. A … Sham Kakade and Jason D. Lee. He works on the theoretical foundations of machine learning, focusing on designing (and implementing) statistically and computationally efficient algorithms. I graduated from the Department of Electrical Engineering, California Institute of Technology (Caltech) where I was adviced by Prof. Babak Hassibi. 3 The Natural Gradient and Policy Iteration We now compare policy improvement under the natural gradient to policy iteration. or. ArXiv Report, arXiv:1809.08530. Sham M. Kakade. Favorites. Authors: Chelsea Finn, Aravind Rajeswaran, Sham Kakade, Sergey Levine. 15 Dec 2020. 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. Sign Up. In ICLR 2020 In NeurIPS, 2018. Sham Kakade (University of Washington; chair), Sanjeev Arora (Princeton University), Kristen Grauman (University of Texas at Austin), Ruslan Salakhutdinov (University … 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? Predicting What You Already Know Helps: Provable Self-Supervised Learning. Sham Kakade is on Facebook. 4. In Summer 2019, I visited Princeton University and worked with Sanjeev Arora on deep learning theory. Paul G. Allen School of Computer Science & Engineering and Department of Statistics, University of Washington 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. About Sham Kakade. Show this thread. Ruosong Wang*, Simon S. Du*, Lin F. Yang*, Sham M. Kakade Conference on Neural Information Processing Systems (NeurIPS) 2020 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. (Partial) Log of changes: Fall 2020: V2 will be consistently updated. In COLT 2020; Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds with Jordan Ash, Chicheng Zhang, Akshay Krishnamurthy and John Langford. Provably Efficient Maximum Entropy Exploration. Efficient Full-Matrix Adaptive Regularization. Rad Niazadeh @rad_niazadeh. In Summer 2020, I interned at Microsoft Research, New York and worked with Sham M. Kakade on reinforcement learning. Naman Agarwal. Our work builds on the synergistic relationship between local model-based control, global value function … PDF We will be updating the book this fall. 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. He co-founded the Algorithmic Foundations of Data Science Institute. Meta-learning views this problem as learning a prior over model parameters that … Contact: Please email us at bookrltheory [at] gmail [dot] com with any typos or errors you find. I did my undergraduate study in Yao Class (2013-2017), Tsinghua University, where I worked closely with Jian Li, Pingzhong Tang and Ran Duan. Provably Correct Automatic Subdifferentiation for Qualified Programs. Sham Kakade retweeted. To connect with Sham, sign up for Facebook today. 33. 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! Alekh Agarwal Nan Jiang Sham M. Kakade Wen Sun. Sham has 1 job listed on their profile. Jason D. Lee, Qi Lei, Nikunj Saunshi, and Jiacheng Zhuo. 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. I am a Research Scientist at Google AI No info to show. We appreciate it! For an appropriate comparison, consider the case in which Q7r (s, a) is … Simon S. Du*, Wei Hu*, Sham M. Kakade*, Jason D. Lee*, Qi Lei* International Conference on Learning Representations (ICLR) 2021. Other. He works on the theoretical foundations of machine learning, focusing on designing provable and practically efficient algorithms. 2018 . 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 Email: naman33k@gmail.com . 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.