BAD 1 - 2 POOR 2 - 3 FAIR 3 - 4 GOOD 4 - 5. Percy Liang is an Associate Professor of Computer Science at Stanford University (B.S. He is an assistant professor of Computer Science and Statistics at Stanford University since 2012, and also the co-founder and renowned AI researcher of Semantic Machines, a Berkeley-based conversational AI startup acquired by Microsoft several months ago. Sham Kakade's statistical learning theory course. 0.00 5.00 /5. BAD GOOD. statistical learning theory course, CS229T/STATS231: Statistical Learning Theory, 9/8: Welcome to CS229T/STATS231! Percy Liang is an Associate Professor of Computer Science at Stanford University (B.S. His two research goals are (i) to make machine learning more robust, fair, and interpretable; and (ii) to make computers easier to … … Percy Liang. of Electrical Engineering and Computer Science, 2005. Featured Co-authors. 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Percy Liang, Assistant Professor of Computer Science at Stanford University, explains that humans rely on some degree of predictability in their day-to-day interactions — both with other humans and automated systems (including, but not limited to, their cars). Year; Squad: 100,000+ questions for machine comprehension of text. /N 100 Percy is related to Zuyang L Liang and Ling Zhang as well as 1 additional person. from MIT, 2004; Ph.D. from UC Berkeley, 2011). [, Wed 11/07: Lecture 14: Online learning, online convex optimization, Follow the Leader (FTL) algorithm hypothesis class [, Wed 10/03: Lecture 4: naive epsilon-cover argument, concentration inequalities /First 813 Title. Percy Liang percyliang. Rate Percy. endobj Wassersetin GANs Current Students and Postdoctoral Researchers Percy Liang is Lead Scientist at Semantic Machines and Assistant Professor of Computer Science at Stanford University. AI Frontiers Conference brings together AI thought leaders to … Includes bibliographical references (p. 75-82). linear algebra, Percy Liang (Preferred) Suggest Name; Emails. [, Mon 10/08: Lecture 5: Sub-Gaussian random variables, Rademacher complexity CS229T/STAT231: Statistical Learning Theory (Winter 2016) Percy Liang Last updated Wed Apr 20 2016 01:36 These lecture notes will be updated periodically as the course goes on. >> Percy Liang. from MIT, 2004; Ph.D. from UC Berkeley, 2011). Reputation Score. [, Mon 10/22: Lecture 9: VC dimension, covering techniques Percy Liang is an Associate Professor of Computer Science at Stanford University (B.S. My goal is to develop trustworthy systems that can communicate effectively with people and improve over time through interaction. Output: for each word type, its cluster (see output.txt for an example). There is no required text for the course. Vandenberghe's Convex Optimization, Sham Kakade's Percy Liang. One way to create this predictability is by taking advantage of machine learning. : Percy Liang The best result we found for your search is Percy Shuo Liang age 30s in Stanford, CA in the Stanford neighborhood. As part of the Trustworthy ML Initiative's seminar series, Percy Liang (Stanford University) presents "Surprises in the Quest for Robust Machine Learning". Free Instagram Followers stochastic setting [, Wed 10/17: Lecture 8: Margin-based generalization error of real analysis, statistical learning theory course, Martin Wainwright's � �T ��f��Ej͏���8���H��8f�@��)���@���D���W�a�\ ��G@Nb���� ��P� [, Mon 11/12: Lecture 15: Follow the Regularized Leader (FTRL) algorithm from MIT, 2004; Ph.D. from UC Berkeley, 2011). Percy Liang's 133 research works with 5,234 citations and 3,995 reads, including: Explore then Execute: Adapting without Rewards via Factorized Meta-Reinforcement Learning Enter email addresses associated with all of your current and historical institutional affiliations, as well as all your previous publications, and the Toronto Paper Matching System. --Massachusetts Institute of Technology, Dept. Percy Liang is an Associate Professor of Computer Science at Stanford University (B.S. There are 4 professionals named "Percy Liang", who use LinkedIn to exchange information, ideas, and opportunities. /Length 1467 and, Machine learning (CS229) or statistics (STATS315A), Convex optimization (EE364A) is recommended, Mon 09/24: Lecture 1: overview, formulation of prediction Search Search. �8YX�.��?��,�8�#���C@%�)�, �XWd��A@ɔ�����B\J�b\��3�/P�p�Q��(���I�ABAe�h��%���o�5�����[u��~���������x���C�~yo;Z����@�o��o�#����'�:� �u$��'���4ܕMWw~fmW��V~]�%�@��U+7F�`޻�r������@�!�U�+G��m��I�a��,]����Ҳ�,�!��}���.�-��4H����+Wu����/��Z9�3qno}ٗ��n�i}��M�f��l[T���K B�Qa;�Onl���e����`�$~���o]N���". Fp(t�� ��%4@@G���q�\ Associate Professor of Computer Science and Statistics (courtesy) Artificial Intelligence Lab Natural Language Processing Group Statistical Machine Learning Group. [, Wed 10/10: Lecture 6: Rademacher complexity, margin theory online learning Michael I. Jordan 185 publications . Sort. If you notice any inaccuracies, please sign in and mark papers as correct or incorrect matches. Percy Liang, 37 Palo Alto, CA. Ms. Percy is affiliated with The University Of Vermont Medical Center and UVM Medical Center Fanny Allen Campus. Approx. >> /Filter /FlateDecode machine learning natural language processing. 378 0 obj << His research spans theoretical machine learning to practical natural language processing; topics include semantic parsing, question answering, machine translation, online learning, method of moments, approximate inference, Bayesian modeling, and deep learning. problems, error decomposition [, Wed 09/26: Lecture 2: asymptotics of maximum likelihood estimators (MLE) [, Mon 10/01: Lecture 3: uniform convergence overview, finite We are testing a new system for linking publications to authors. Percy Liang. Assistant Professor of Computer Science, Stanford University. … You can help! [, Wed 12/05: Lecture 20: Information theory, regret bound for probability theory, Tatsunori Hashimoto (Stanford University, post-doc, jointly supervised with Percy Liang, 2016{2019). endstream [, Mon 12/03: Lecture 19: Regret bound for UCB, Bayesian setup, [, Wed 10/24: Lecture 10: Covering techniques, overview of GANs No matching publications found. from MIT, 2004; Ph.D. from UC Berkeley, 2011). Research Areas. x���o�6���+t��Z��.CV��=�;02c���#M�חI�q�6Z���N�h�����%-#�y��6��5d�)��D��H�qq�SL�"��. Boyd and Vandenberghe's Convex Optimization. [Please refer to, Mon 10/29: Lecture 11: Total variation distance, Wasserstein distance, Wasserstein GANs #�;���$���J�Y����n"@����)|��Ϝ�L�?��!�H�&� ��D����@ %BHa�`�Ef�I�S��E�� �T Block user. from MIT, 2004; Ph.D. from UC Berkeley, 2011). Search for Percy Liang's work. stream Associate Professor of Computer Science and Statistics. Understanding and Mitigating the Tradeoff Between Robustness and Accuracy Aditi Raghunathan * 1Sang Michael Xie Fanny Yang2 John C. Duchi 1Percy Liang … Block user Report abuse. Learn more about blocking users. Check out what Percy Liang will be attending at NIPS 2014 See what Percy Liang will be attending and learn more about the event taking place Dec 7, 2014 - Dec 12, 2015 . His two research goals are (i) to make machine learning more robust, fair, and interpretable; and (ii) to make computers easier to communicate with through natural language. Percy Liang. [, Mon 10/15: Lecture 7: Rademacher complexity, neural networks Prevent this user from interacting with your repositories and sending you notifications. In this paper, we use influence functions -- a classic technique from robust statistics -- to trace a model's prediction through the learning algorithm and back to its training data, thereby identifying training points most responsible for a given prediction. [, Wed 11/28: Lecture 18: Multi-armed bandit problem in the 24. results. If you identify any major omissions or other inaccuracies in the publication list, please let us know. Cited by. %PDF-1.5 Eng.) Ms. Percy works in Burlington, VT and 1 other location and specializes in Family Medicine. Understanding and mitigating the tradeoff between robustness and accuracy.Aditi Raghunathan, Sang Michael Xie, Fanny Yang, John C. Duchi, Percy Liang.arXiv preprint arXiv:2002.10716, 2020. Skip slideshow. They have also lived in Palo Alto, CA and Berkeley, CA. His two research goals are (i) to make machine learning more robust, fair, and interpretable; and (ii) to make computers … [. Percy Liang Thesis (M. Implementation of the Brown hierarchical word clustering algorithm. Previous years' home pages are, Uniform convergence (VC dimension, Rademacher complexity, etc), Implicit/algorithmic regularization, generalization theory for neural networks, Unsupervised learning: exponential family, method of moments, statistical theory of GANs, A solid background in Percy Liang. Approximate Reputation Score. claim profile ∙ 0 followers Stanford University Assistant Professor at Stanford University. %���� [, Wed 11/14: Lecture 16: FTRL in concrete problems: online regression & expert problem, convex to linear reduction Peter Bartlett's statistical learning theory course. [, Wed 10/31: Lecture 12: Generalization and approximation in Thompson sampling This information is crucial for deduplicating users, and ensuring you see your reviewing assignments. /Filter /FlateDecode xڥW�r�6}�W�����$;�t\7�N�c��_ �0�������H'�cStg, g���]��"�IEdH�(1$""#�HĚ�RI"!��HI� A number of useful references: Percy Liang's course notes from previous Associate Professor of Computer Science, Stanford University. /Type /ObjStm /Length 1337 2 0 obj << Photos | Summary | Follow. His two research goals are (i) to make machine learning more robust, fair, and interpretable; and (ii) to make computers easier to communicate with through natural language. Percy Liang Release 1.3 2012.07.24 Input: a sequence of words separated by whitespace (see input.txt for an example). His two research goals are (i) to make machine learning more robust, fair, and interpretable; and (ii) to make computers easier to communicate with through natural language. Bio Associate Professor in CS @Stanford @stanfordnlp | Pianist Lokasyon Stanford, CA Tweets 11 Followers 2,7K Following 197 Account created 31-10-2009 07:26:37 ID 86481377. Cited by. Gates 250 / pliang@cs.stanford.edu [Publications] Research. View the profiles of people named Percy Liang. Bio. �R�[���8���ʵHaQ�W�ǁl�S����}�֓����]�HF��C#�F���/K����+��֮������#�I'ꉞ�'TcϽ�G�\�7�����-��m��}�;G����6�?�paC��i\�W.���-�x��w�-�ON�iC;��؈V��N����3�5c�Ls7�`���6[���Y�C^�ܕv�q-Xb����nPv8�d��pvw��jU��گ<20j膿�(���ߴ� CK���:A�@����Q����V}�t-��\o�j�M�q�V9-���w�H��K�P{�f�HCO�qzv�s�Cxh�Y8C7�ZA˦uݮ�qJ=,yl��7=|�~���$��9.F7.�Dxz��;��G�V���8|�[˝�U�q�:G|N��G/�ӈzLb��y�������Qh�j���w�{�{ �Ptƛi�x؋TLB�S�~�Ɇx��)��N|��a�OϾ{ ��DJ�O{��`�f �|�`��j7c&aƫO�$�9{���q�C�/��]�^��t�����/���� Follow. View the profiles of professionals named "Percy Liang" on LinkedIn. stream Sort by citations Sort by year Sort by title. Home Percy Liang. 122. papers. How can we explain the predictions of a black-box model? Dr. Percy Liang is the brilliant mind behind SQuAD; the creator of core language understanding technology behind Google Assistant. Home Research-feed … [, Thu 11/01: Homework 2 (uniform convergence), Mon 11/05: Lecture 13: Restricted Approximability, overview of Percy Liang's course notes from previous offerings of this course. Percy Liang is an Associate Professor of Computer Science at Stanford University (B.S. Fanny Yang (Stanford University, post-doc, jointly supervised with Percy Liang, 2019). offerings of this course, Peter Bartlett's statistical learning theory course, Boyd and Select this result to view Percy Shuo Liang's phone number, address, and more. 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