Cornell Learning Machines Seminar
The Cornell Learning Machines Seminar is a semi-monthly seminar held at the Cornell Tech campus in New York City. The seminar focuses on machine learning and related areas, including Natural Language Processing, Vision, and Robotics.
To receive seminar announcements, please subscribe to our mailing list by emailing cornell-lmss-l-request@cornell.edu with the subject "join".
The talks take place on the Cornell Tech campus. The room and time are specified for each talk. Attending requires to RSVP in advance. If coming from outside, please arrive a few minutes in advance to check into the building. Directions to campus are provided here.
Organized by Yoav Artzi
This seminar is sponsored by
Upcoming Talks
Past Talks
- Sherry Tongshuang Wu (CMU) / Practical AI Systems: From General-Purpose AI to (the Right) Specific Use Cases / Oct 31, 2024 [video coming soon]
- Andrew Owens (University of Michigan) / Generating Multi-View Visual Illusions / Oct 24, 2024 [video coming soon]
- Himabindu Lakkaraju (Harvard) / Towards Regulatable AI: Algorithmic Challenges and Opportunities / Oct 17, 2024 [video coming soon]
- Xiaolong Wang (UC San Diego) / Learning Humanoid Robots / Sep 19 2024 [video coming soon]
- Raymond Mooney (UT Austin) / Using Natural Language to Help Train Robots / Mar 8, 2024 [video coming soon]
- Amir Globerson (Tel Aviv University) / Knowledge in Large Language Models: Quantification, Validation and Dissection / Feb 2, 2024 [video coming soon]
- Eunsol Choi (UT Austin) / Knowledge Augmentation for Language Models / Nov 17, 2023 [video coming soon]
- Yoon Kim (MIT) / Large Language Models & Symbolic Structures / Nov 10, 2023 [video coming soon]
- Mark Yatskar (UPenn) / Inherent Interpretability via Language Model Guided Bottleneck Design / Oct 27, 2023 [video coming soon]
- Jacob Andreas (MIT) / Language Models as World Models? / Oct 13, 2023 [video coming soon]
- Yejin Choi (UW) / Common Sense: the Darker Matter of Language and Intelligence / Sep 8, 2023 [video coming soon]
- David Blei (Columbia) / Scaling and generalizing approximate Bayesian inference / April 28, 2023 [video]
- Yiling Chen (Harvard) / Forecast Aggregation: Sample Complexity and Peer-Assessment-Based Improvements / April 21, 2023 [video]
- Phebe Vayanos (University of Southern California) / Learning Optimal Policies for Online Allocation of Scarce Housing Resources from Data Collected in Deployment / April 14, 2023 [video]
- Ruth Misener (Imperial College London) / Between formulations or: How I Learned to Stop Worrying and Love Parameters / February 17, 2023 [video]
- Petar Durdevic (Aalborg University) / Waste Deep – Using Deep Learning methods to improve Wastewater Treatment / December 2, 2022 [video]
- Yoshua Bengio (Université de Montreal) / Reusable Modular and Causal Knowledge Representation for Lifelong Learning / November 4, 2022 [video]
- Vivek Farias (MIT) / Markovian Interference and the Differences-in-Qs Estimator / October 28, 2022 [video]
- Wei Xu (Georgia Tech) / Importance of Data and Controllability in Neural Language Generation / September 23, 2022 [video]
- Shuran Song (Columbia University) / Active Scene Understanding with Robot Interactions / March 5, 2021 [video]
- Sameer Singh (University of California, Irvine) / Evaluating and Testing Natural Language Processing Models / February 26, 2021 [video]
- Raquel Fernández (University of Amsterdam) / Individual and Social Processes in Image Description Generation / February 19, 2021 [video]
- Jason Baldridge (Google Research) / Language Lifts Experience / December 4, 2020 [video]
- Yonatan Bisk (CMU) / ALFRED -- A Simulated Playground for Connecting Language, Action, and Perception / October 23, 2020 [video]
- Zhou Yu (UC Davis) / Personalized Persuasive Dialog Systems / September 18, 2020
- Kyunghyun Cho (NYU/Facebook AI Research) / Inconsistency of a Recurrent Language Model: a Question I Forgot to Ask in 2014 / March 6, 2020 [video]
- Tom Kwiatkowski (Google AI) / New Challenges in Question Answering: Natural Questions and Going Beyond Word Matching / February 21, 2020
- Danqi Chen (Princeton) / Advancing Textual Question Answering / January 31, 2020
- Sam Bowman (NYU) / Task-Independent Language Understanding / September 27, 2019 [video]
- Kathleen McKeown (Columbia) / Where Natural Language Processing Meets Societal Needs / September 19, 2019 (joint with DLI seminar)
- Noah Smith (UW/AI2) / Rational Recurrences for Empirical Natural Language Processing / September 13, 2019 [video]
- Kristen Grauman (UT Austin/Facebook AI Research) / Anticipating the Unseen and Unheard for Embodied Perception / March 8, 2019 [video]
- Richard Socher (Salesforce) / The Natural Language Decathlon: Multitask Learning as Question Answering / February 22, 2019 [video]
- Percy Liang (Stanford) / Can Language Robustify Learning? / February 8, 2019
- Bill Freeman (Google/MIT) / Learning from Sight and Sound / February 1, 2019 [video]
- Igor Labutov (LAER AI) / Teaching Machines like we Teach People / October 26, 2018
- Dan Roth (U Penn) / Natural Language Understanding with Incidental Supervision / September 21, 2018 [video]
- Byron Boots (Georgia Tech) / Learning Perception and Control for Agile Off-Road Autonomous Driving / March 9, 2018 [video]
- Olga Russakovsky (Princeton) / The Human Side of Computer Vision / February 23, 2018 [video]
- Raymond Mooney (UT Austin) / Robots that Learn Grounded Language Through Interactive Dialog / Oct 6, 2017 [video]