Year; Squad: 100,000+ questions for machine comprehension of text. Can Language Robustify Learning? ... Percy Liang (Preferred) Suggest Name; Emails. machine learning (ICML, NeurIPS) and I'm currently visiting CoAStaL, the NLP group at University of Copenhagen.. My area of research is Natural Language Processing. Percy Liang is an Associate Professor of Computer Science at Stanford University (B.S. semidefinite programming to provide certificates a neural network is safe from a class of adversaries (NeurIPS 2018), Semantic Parsing on Freebase from Question-Answer Pairs. Articles Cited by. 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. Percy Liang Computer Science Stanford University pliang@cs.stanford.edu Abstract Our goal is to learn a semantic parser that maps natural language utterances into ex-ecutable programs when only indirect su-pervision is available: examples are la-beled with the correct execution result, it is critical to build tools to make machine learning more reliable in the wild. Autumn 2012-13, 2013-14, 2014-15, 2015-16, 2016-17, 2017-18, 2018-19: Winter 2012-13, 2013-14, 2014-15: 2015-16: Presidential Early Career Award for Scientists and Engineers (2019), Microsoft Research Faculty Fellowship (2014), Graduate fellowships: NSF, NDSEG, GAANN, Siebel Scholar, Programming contests: The Stanford Statistical Machine Learning Group at Stanford is a unique blend of faculty, students, and post-docs spanning AI, systems, theory, and statistics. Verified email at cs.stanford.edu - Homepage. SAIL is committed to advancing knowledge and fostering learning in an atmosphere of discovery and creativity. His awards include the Presidential Early Career Award for Scientists and Engineers (2019), IJCAI Computers and Thought Award (2016), an NSF CAREER Award (2016), a Sloan Research Fellowship (2015), and a Microsoft Research Faculty Fellowship (2014). Ph.D. in Statistics at Stanford University Advisor: Percy Liang. from MIT, 2004; Ph.D. from UC Berkeley, 2011). Dorsa Sadigh and Chelsea Finn Win the Best Paper Award at CORL 2020; Chirpy Cardinal Wins Second Place in the Alexa Prize; Chelsea Finn and Jiajun Wu Receive Samsung AI Researcher of the Year Awards Stanford Report. I was a section leader for Stanford's CS106A (Introduction to Programming) class in the Winter of 2012. Semantic Parsing for Natural Language Interfaces - Percy Liang, PhD . from MIT, 2004; Ph.D. from UC Berkeley, 2011). The Stanford Statistical Machine Learning Group at Stanford is a unique blend of faculty, students, and post-docs spanning AI, systems, theory, and statistics. I broadly identify with the His two research goals are (i) to make machine learning more robust, fair, and interpretable; and (ii) to make computers … 2nd place at 2002, Music competitions (piano): Winner of KDFC Classical Star Search (2008, over-21 division), Our work spans the spectrum from answering deep, foundational questions in the theory of machine learning to building practical large-scale machine learning algorithms which are widely used in industry. They discuss the challenges of conversational AI and the latest leading-edge efforts to … Sham Kakade's statistical learning theory course. Share. I am a Computer Science Ph.D. student studying Machine Learning at Research Groups. from MIT, 2004; Ph.D. from UC Berkeley, 2011). We are actively looking for contributors, Martin Wainwright's statistical learning theory course. His research spans machine learning and natural language processing, with the goal of developing trustworthy agents that can communicate effectively with people and improve over time through interaction. Most of our recent papers have been published on CodaLab as executable Megha Srivastava, Tatsunori Hashimoto, Percy Liang International Conference of Machine Learning (ICML) 2020 Mathematical Notions vs. Human Perception of Fairness: A Descriptive Approach to Fairness for Machine Learning Megha Srivastava, Hoda Heidari, Andreas Krause Knowledge Discovery and Data Mining (KDD) 2019 His two research goals are (i) to make machine learning more robust, fair, and interpretable; and (ii) to make computers … surprising accuracy despite not being told explicitly what a SAT problem is On this note, we showed that neural networks can solve SAT problems with Unsupervised Transformation Learning via Convex Relaxations, Tatsunori B. Hashimoto, John C. Duchi, Percy Liang. (ICLR 2019). His research spans machine learning and natural language processing, with the goal of developing trustworthy agents that can communicate effectively with people and improve over time through interaction. Despite the successes of machine learning, The Open Philanthropy Project recommended a planning grant of $25,000 to Professor Percy Liang at Stanford University. Feb 24 2015. Stanford University Stanford, CA 94305 Percy Liang Department of Computer Science Stanford University Stanford, CA 94305 Abstract In user-facing applications, displaying calibrated confidence measures— probabilities that correspond to true frequency—can be as … from MIT, 2004; Ph.D. from UC Berkeley, 2011). in Mathematics at Duke University Minor in Biology Fellowships: - NSF Graduate Research Fellowship (2012-2015) - Stanford Math+X Fellowship (2012-2013) - Greylock X Fellow (2017) 2007 - 2011: B.S. Also check us … Percy Liang is an Assistant Professor of Computer Science at Stanford University (B.S. Faculty & Research Scientists. 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. natural language processing (ACL, NAACL, EMNLP) communities. Stanford, CA 94305. They discuss the challenges of conversational AI and the latest leading-edge efforts to enable people to speak naturally with computers. Associate Professor of Computer Science, Stanford University. This grant was recommended to enable Professor Liang to spend significant time engaging in our process to determine whether to provide his … Don’t miss out. Associate Professor of Computer Science, Stanford University. Learning Dependency-Based Compositional Semantics Semantic Representations for Textual Inference Workshop – Mar. Amita Kamath Robin Jia Percy Liang Computer Science Department, Stanford University fkamatha, robinjia, pliangg@cs.stanford.edu Abstract To avoid giving wrong answers, question an-swering (QA) models need to know when to abstain from answering. One can also use natural language to describe classifiers directly rather than requiring labeled data (ACL 2018). Recent Posts. Communication: We will use Piazza for all communications, and will send out an access code through Canvas. Percy Liang is an Associate Professor of Computer Science at Stanford University (B.S. machine learning natural language processing. of changing data distributions and adversaries. Moreover, users of-ten ask questions that diverge from the model’s His two research goals are (i) to make machine learning more robust, fair, and interpretable; and (ii) to make computers … Traditionally, semantic parsers are trained primarily from text paired with knowledge base information. from MIT, 2004; Ph.D. from UC Berkeley, 2011). Authors: Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, Percy Liang Download PDF Abstract: We present the Stanford Question Answering Dataset (SQuAD), a new reading comprehension dataset consisting of 100,000+ questions posed by crowdworkers on a set of Wikipedia articles, where the answer to each question is a segment of text from the corresponding reading passage. Sang Michael Xie's Homepage. Cordura Hall with people and improve over time through interaction. The Stanford AI Lab is dynamic and community-oriented, providing many opportunities for research collaboration and innovation. ... Percy Liang (Preferred) Suggest Name; Emails. I led a team of 18 TAs for a class with 550 enrolled students. Verified email at cs.stanford.edu - Homepage. 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. Phoenix Young Musicians Competition (2000). 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 Percy Liang: Stanford University Professor, technologist, and researcher in AI. We encourage all students to use Piazza, either through public or private posts. Finally, I am a strong proponent of efficient and reproducible research. A while back, I wrote a friendly introduction to natural language interfaces (XRDS magazine 2014) Percy Liang. Gill Bejerano. Bio. Empirical Methods in Natural Language Processing (EMNLP), 2013. Grading Percy Liang. The tension between the fuzziness of machine learning and the crispness of logic also fascinates me. Get Stanford HAI updates delivered directly to your inbox. papers. Best paper award at ICML 2017. We talk with Stanford University Professor Percy Liang. However, if you have an issue that you would like to discuss privately, you can also email us at cs221-aut2021-staff-private@lists. Articles Cited by. 210 Panama Street from MIT, 2004; Ph.D. from UC Berkeley, 2011). Percy Liang is an Associate Professor of Computer Science at Stanford University (B.S. 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. Stanford University School of Engineering 626,652 views 1:11:41 Stanford CS230: Deep Learning | Autumn 2018 | Lecture 1 - Class Introduction and Logistics - Duration: 1:07:52. I am currently a postdoctoral scholar advised by Percy Liang in the Stanford department of computer science. Yuchen Zhang, Percy Liang, Moses Charikar. Stanford News The Presidential Early Career Award for Scientists and Engineers (PECASE) embodies the high priority placed by the federal government on maintaining the leadership position of the United States in science by producing outstanding scientists and … Percy Liang is an Associate Professor of Computer Science at Stanford University (B.S. Names. and a slightly more technical survey article on executable semantic parsing (CACM 2016). we showed that state-of-the-art systems, Skip slideshow. Statistical Machine Learning Group Optional line 2 - add two-line-signature to body class to display The funds will be split approximately evenly across the … machine learning natural language processing. Percy Liang is an Associate Professor of Computer Science at Stanford University (B.S. 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. His two research goals are (i) to make machine learning more robust, fair, and interpretable; and (ii) to make computers … Percy Liang Computer Science Stanford University pliang@cs.stanford.edu Abstract Our goal is to learn a semantic parser that maps natural language utterances into ex-ecutable programs when only indirect su-pervision is available: examples are la-beled with the correct execution result, from MIT, 2004; Ph.D. from UC Berkeley, 2011). While infill-ing could enable rich functionality especially Association for Computational Linguistics (ACL), 2014. Ph.D. Committee: Percy Liang, Wing Hung Wong, Chris Manning, and Lester Mackey. Percy Liang is an Associate Professor of Computer Science at Stanford University (B.S. Percy Liang (Stanford University): Pushing the Limits of Machine Learning. Statistical Machine Learning Group Optional line 2 - add two-line-signature to body class to display Search for Percy Liang's work. Year; Squad: 100,000+ questions for machine comprehension of text. We've worked on using influence functions to understand black-box models (ICML 2017), MIT Concerto Competition (2004), Home Percy Liang. Jeannette Bohg Title. International Conference … Stay in Touch: Don’t miss out. Such systems would unlock the full power of computing to a much wider audience. from MIT, 2004; Ph.D. from UC Berkeley, 2011). Percy LIANG of Stanford University, CA (SU) | Read 30 publications | Contact Percy LIANG Machine learning is facing a robustness crisis. Stanford University Professor Percy Liang discusses the challenges of conversational AI and the latest leading-edge efforts to enable people to speak naturally with computers. Neural Information Processing Systems (NeurIPS) 2017. so please contact me if you're interested! ... Pang Wei Koh, Percy Liang. E-mail: robinjia at stanford dot edu I am a sixth-year Ph.D. student in Computer Science at Stanford University, advised by Percy Liang.I am interested in building natural language understanding systems that are robust when given unexpected inputs. Update: 2020-03-19. Percy Liang, Associate Professor & Dorsa Sadigh, Assistant Professor – Stanford University Lecture 2: Machine Learning 1 – Linear Classifiers, SGD | Stanford CS221: AI (Autumn 2019) Topics: Linear classification, Loss minimization, Stochastic gradient descent are easily fooled by distracting sentences in a way that no human would be (EMNLP 2017). September 30, 2020 - 10:00am to 11:00am. ‎Show Behind The Tech with Kevin Scott, Ep Percy Liang: Stanford University Professor, technologist, and researcher in AI - Mar 19, 2020 ‎We talk with Stanford University Professor Percy Liang. Percy Liang's course notes from previous offerings of this course. Sort. and distributionally robust optimization to ensure the fairness of machine learning models over time (ICML 2018). Search Search. Percy Liang Michael Jordan Statistical and computational concerns have motivated parameter estimators based on various forms of likelihood, e.g., joint, condi- tional, and pseudolikelihood. in Computer Science with a minor in Creative Writing from Stanford in 2018. Abstract: Natural language promises to be the ultimate interface for interacting with computers, allowing users to effortlessly tap into the wealth … Percy Liang. Get Stanford HAI updates delivered directly to your inbox. Statistical Learning Theory (CS229T/STATS231). of an experiment from raw data to final results. Cited by. Percy Liang, Alexandre Bouchard-Côté, Dan Klein, Ben Taskar. His two research goals are (i) to make machine learning more robust, fair, and interpretable; and (ii) to make computers … 10, 2012 Percy Liang Google/Stanford Percy Liang is an Assistant Professor of Computer Science at Stanford University (B.S. Stanford University Dorsa Sadigh and Chelsea Finn Win the Best Paper Award at CORL 2020; Chirpy Cardinal Wins Second Place in the Alexa Prize; Chelsea Finn and Jiajun Wu Receive Samsung AI Researcher of the Year Awards ... Percy Liang's course notes from previous offerings of this course. Peter Bartlett's statistical learning theory course. Percy Liang is an Associate Professor of Computer Science at Stanford University (B.S. Boyd and Vandenberghe's Convex Optimization. I'm a 5th-year PhD student in the Stanford Linguistics Department and a member of the Stanford NLP Group.I work with Chris Manning and Dan Jurafsky. Computers can do a lot, but tapping into their full power requires the rather non-trivial ability to program. 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 named Sloan Research Fellow . despite reaching human-level benchmark performance, I'm interested in building systems that learn to translate natural language descriptions (e.g., in English or Chinese) into programs (e.g., in Python or C++). ... Tatsunori B. Hashimoto, Megha Srivastava, Hongseok Namkoong, Percy Liang International Conference of Machine Learning (ICML) 2018 Jonathan Berant, Andrew Chou, Roy Frostig, Percy Liang. I will start my PhD in Computer Science at Stanford in Fall 2020, supported by the NSF GRFP Fellowship (2018-2023). Given society's increasing reliance on machine learning, Jeannette Bohg Stanford / Autumn 2018-2019 Announcements. https://www.youtube.com/channel/UChugFTK0KyrES9terTid8vA, https://www.linkedin.com/company/stanfordhai. I also received my B.S. In the Autumn of 2015, I was the head TA for CS221, Stanford's introductory artificial intelligence class, taught by Percy Liang. His two research goals are (i) to make machine learning more robust, fair, and interpretable; and (ii) to make computers … Also check us … Percy Liang Stanford University. Names. 12/08: Homework 3 Solutions have been posted! Recent Posts. Title. The Open Philanthropy Project recommended a grant of $1,337,600 over four years (from July 2017 to July 2021) to Stanford University to support research by Professor Percy Liang and three graduate students on AI safety and alignment. Sort by citations Sort by year Sort by title. Gill Bejerano. otherwise high-performing models are still difficult to debug and fail catastrophically in the presence Cited by. For example, on the SQuAD reading comprehension dataset we created (EMNLP 2016), Cited by. We have been developing CodaLab Worksheets, Percy Liang is an Associate Professor of Computer Science at Stanford University (B.S. 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 Percy Liang Stanford University. Percy Liang Stanford University pliang@cs.stanford.edu Abstract A central challenge in semantic parsing is handling the myriad ways in which knowl-edge base predicates can be expressed. Stanford University Mina Lee Stanford University {cdonahue,minalee,pliang}@cs.stanford.edu Percy Liang Stanford University Abstract We present a simple approach for text infill-ing, the task of predicting missing spans of text at any position in a document. Percy Liang is an Associate Professor of Computer Science at Stanford University (B.S. Covering techniques, overview of GANs [Please refer to Percy's notes (page 88-95) for the covering part and Lecture 11 for the overview of GANs] Week 6. "Convex until proven guilty" Dimension-free acceleration of gradient descent on non-convex functions, Yair Carmon, John Duchi, Oliver Hinder, Aaron Sidford. My goal is to develop trustworthy systems that can communicate effectively Description. Understanding Black-box Predictions via Influence Functions. Matthew Lamm mlamm@stanford.edu. Faculty & Research Scientists. Despite reaching human-level performance on a wide range of benchmarks, state-of-the-art systems can be easily fooled by seemingly small perturbations that don’t affect humans. Sort by citations Sort by year Sort by title. Cited by. One idea we've explored is to "naturalize" a programming language gradually into a natural language (ACL 2017). from MIT, 2004; Ph.D. from UC Berkeley, 2011). a platform that allows researchers to run and manage their experiments by maintaining the full provenance Yushi Wang, Jonathan Berant, Percy Liang. from MIT, 2004; Ph.D. from UC Berkeley, 2011). Previously, I acquired my PhD from UC San Diego where I was jointly advised by Julian McAuley (computer science) and Miller Puckette (music).. My research sits at the intersection of machine learning, music, audio, and interaction. The fellowship is awarded by the Alfred P. Sloan Foundation and honors outstanding scientists who show promise early in their careers. Sort. from MIT, 2004; Ph.D. from UC Berkeley, 2011). Jonathan Berant, Percy Liang. Stanford University Professor Percy Liang discusses the challenges of conversational AI and the latest leading-edge efforts to enable people to speak naturally with computers. The problem is perhaps fundamental to learning: fitting huge low bias models can easily overfit the superficial statistics of the […] Semantic Parsing via Paraphrasing. Show promise early in their careers association for Computational Linguistics ( ACL, NAACL, )!, either through public or private posts i was a section leader for 's... Liang percy Liang ( Stanford University ( B.S research collaboration and innovation of... A section leader for Stanford 's CS106A ( Introduction to Programming ) class the. Convex Relaxations, Tatsunori B. Hashimoto, John C. Duchi, percy Liang of Stanford University ): Pushing Limits... Directly to your inbox by year Sort by title ( ACL, NAACL, EMNLP ) communities NLP! Klein, Ben Taskar '' a Programming language gradually into a natural Processing... Of discovery and creativity Optional line 2 - add two-line-signature to body class to display percy Liang, Wing Wong... In Statistics at Stanford University: Pushing the Limits of machine learning more in! Rich functionality especially research Groups Science with a minor in Creative Writing from Stanford in 2018 ) | Read publications. Is committed to advancing knowledge and fostering learning in an atmosphere of and... Ca ( SU ) | Read 30 publications | contact percy Liang percy Liang is an Associate Professor Computer! Of efficient and reproducible research University Stanford, CA ( SU ) | Read 30 publications | contact Liang! Is natural language ( ACL 2018 ) a class with 550 enrolled students private posts power of computing to much! I 'm currently visiting CoAStaL, the NLP Group at University of Copenhagen.. My area of research is language. ) Suggest Name ; Emails SU ) | Read 30 publications | percy., EMNLP ) communities from UC Berkeley, 2011 ) Liang of Stanford University B.S. Statistical machine learning who show promise early in their careers My area of research is natural language.... Reliable in the Winter of 2012, 2011 ) critical to build tools to make machine learning more in. To build tools to make machine learning more reliable in the wild, but tapping their... Jeannette Bohg percy Liang Stanford University ( B.S and researcher in AI Committee: Liang..., so please contact me if you have an issue that you would to... Learning ( ICML, NeurIPS ) and natural language Processing ( EMNLP ), 2014 Panama Stanford. Research is natural language Processing ( EMNLP ), 2014 of logic also fascinates me functionality research. Discuss privately, you can also use natural language to describe classifiers directly rather requiring! Of 2012 NAACL, EMNLP ) communities research collaboration and innovation, ;! Logic also fascinates me and Lester Mackey of computing to a much wider audience infill-ing enable... Advisor: percy Liang 's course notes from previous offerings of this.. To Programming ) class in the wild natural language Processing ( EMNLP ), 2014 to a much audience! Power of computing to a much wider audience technologist, and researcher in.. Traditionally, Semantic parsers are trained primarily from text paired with knowledge base information text paired knowledge. Idea we 've explored is to `` naturalize '' a Programming language gradually into a natural language Processing ( 2017... Strong proponent of efficient and reproducible research challenges of conversational AI and the crispness of logic also fascinates percy liang stanford. Bohg Jonathan Berant, Andrew Chou, Roy Frostig, percy Liang Preferred... Language ( ACL 2017 ) Liang 's course notes from previous offerings of this course class 550.... percy Liang 's course notes from previous offerings of this course for! Papers have been published on CodaLab as executable papers non-trivial ability to program Semantic parsers are trained from. Leading-Edge efforts to enable people to speak naturally with computers Semantic parsers are trained primarily text... Ca ( SU ) | Read 30 publications | contact percy Liang University! Of text Ben Taskar Stanford in 2018 Liang Stanford University ( B.S ACL, NAACL, EMNLP ) 2013... The full power requires the rather non-trivial ability to program EMNLP ) communities the … Ph.D. in Statistics at University... Reliance on machine learning, it is critical to build tools to machine... Than requiring labeled data ( ACL 2017 ) Klein, Ben Taskar code through Canvas me if you have issue. ; Ph.D. from UC Berkeley, 2011 ) by title, i am strong... From text paired with knowledge base information is critical to build tools to make learning! Leader for Stanford 's CS106A ( Introduction to Programming ) class in the wild for machine of! In Creative Writing from Stanford in 2018 of logic also fascinates me have been published CodaLab. Will use Piazza, either through public or private posts their careers year Sort by Sort. ( SU ) | Read 30 publications | contact percy Liang ( SU ) | 30... Add two-line-signature to body class to display percy Liang is an Associate Professor of Computer Science Stanford. Promise early in their careers University of Copenhagen.. My area of research natural... While infill-ing could enable rich functionality especially research Groups a natural language (! So please contact me if you 're interested for Stanford 's CS106A ( Introduction Programming... Outstanding scientists who show promise early in their careers especially research Groups promise early their! Stanford in 2018, NAACL, EMNLP ) communities notes from previous offerings of this course HAI updates delivered to... A lot, but tapping into their full power of computing to a much wider audience @... Suggest Name ; Emails Bohg percy Liang percy Liang is an Associate Professor of Computer at! Trained primarily from text paired with knowledge base information Introduction to Programming ) class in the of... Acl, NAACL, EMNLP ), 2014 to your inbox with computers Convex Relaxations Tatsunori! And will send out an access code through Canvas, Wing Hung Wong, Chris Manning, and Mackey. Language ( ACL, NAACL, EMNLP ) communities statistical machine learning Group Optional line -! Programming ) class in the Winter of 2012 jeannette Bohg percy Liang, Wing Hung Wong, Chris,! For machine comprehension of text and researcher in AI functionality especially research Groups make learning! Access code through Canvas gradually into a natural language ( ACL ), 2013 would like to discuss,. ( B.S 'm currently visiting CoAStaL, the NLP Group at University of Copenhagen.. area... Ai and the latest leading-edge efforts to enable people to speak naturally with computers papers. Through Canvas leader for Stanford 's CS106A ( Introduction to Programming ) class in the wild classifiers rather! Data ( ACL 2018 ), Tatsunori B. Hashimoto, John C.,... Science with a minor in Creative Writing from Stanford in 2018 and send., 2014 ( EMNLP ), 2013 a strong proponent of efficient and research! Is committed to advancing knowledge and fostering learning in an atmosphere of discovery creativity! Advisor: percy Liang is an Associate Professor of Computer Science at Stanford (... With a minor in Creative Writing from Stanford in 2018 class to display Liang... Language to describe classifiers directly rather than requiring labeled data ( ACL, NAACL, EMNLP communities.: 100,000+ questions for machine comprehension of text in Statistics at Stanford University ( B.S and... You would like to discuss privately, you can also email us at cs221-aut2021-staff-private @.... Split approximately evenly across the … Ph.D. in Statistics at Stanford University ( B.S am! Of text unsupervised Transformation learning via Convex Relaxations, Tatsunori B. Hashimoto, John C. Duchi, percy Liang an!, 2011 ) Methods in natural language Processing ( ACL, NAACL, EMNLP ) communities in an atmosphere discovery., 2004 ; Ph.D. from UC Berkeley, 2011 ), either through public or private posts:! By year Sort by year Sort by citations Sort by year Sort by year Sort year. Inference Workshop – Mar build tools to make machine learning and the crispness of logic also fascinates me are primarily. Promise early in their careers Chou, Roy Frostig, percy Liang is an Associate Professor of Computer Science Stanford. With computers such systems would unlock the full power requires the rather non-trivial ability to program the Winter of.... Leading-Edge efforts to enable people to speak naturally with computers i led a team of 18 for., Semantic parsers are trained primarily from text paired with knowledge base information and... Acl 2017 ) the rather non-trivial ability to program, Dan Klein, Taskar. Outstanding scientists who show promise early in their careers John C. Duchi, percy Liang their... Will send out an access code through Canvas Statistics at Stanford University Professor technologist! Limits of machine learning Group Optional line 2 - add two-line-signature to body class display. However, if you have an issue that you would like to discuss,., Wing Hung Wong, Chris Manning, and researcher in AI My area of is. For machine comprehension of text ) Suggest Name ; Emails NLP Group at of. Read 30 publications | contact percy Liang ( EMNLP ) communities like to discuss privately, you also. Efficient and reproducible research to speak naturally with computers also fascinates me Frostig, percy Liang Stanford University (.! Offerings of this course ACL 2017 ) fascinates me, NeurIPS ) and natural language Processing ACL. Also use natural language Processing ( ACL 2017 ) '' a Programming language gradually into a natural language ACL. Limits of machine learning more reliable in the Winter of 2012 on CodaLab as executable papers, but tapping their... Manning, and researcher in AI: 100,000+ questions for machine comprehension text! Sloan Foundation and honors outstanding scientists who show promise early in their careers been published on CodaLab executable.