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On the Opportunities and Risks of Foundation Models


Aug 18, 2021
Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S. Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, Erik Brynjolfsson, Shyamal Buch, Dallas Card, Rodrigo Castellon, Niladri Chatterji, Annie Chen, Kathleen Creel, Jared Quincy Davis, Dora Demszky, Chris Donahue, Moussa Doumbouya, Esin Durmus, Stefano Ermon, John Etchemendy, Kawin Ethayarajh, Li Fei-Fei, Chelsea Finn, Trevor Gale, Lauren Gillespie, Karan Goel, Noah Goodman, Shelby Grossman, Neel Guha, Tatsunori Hashimoto, Peter Henderson, John Hewitt, Daniel E. Ho, Jenny Hong, Kyle Hsu, Jing Huang, Thomas Icard, Saahil Jain, Dan Jurafsky, Pratyusha Kalluri, Siddharth Karamcheti, Geoff Keeling, Fereshte Khani, Omar Khattab, Pang Wei Kohd, Mark Krass, Ranjay Krishna, Rohith Kuditipudi, Ananya Kumar, Faisal Ladhak, Mina Lee, Tony Lee, Jure Leskovec, Isabelle Levent, Xiang Lisa Li, Xuechen Li, Tengyu Ma, Ali Malik, Christopher D. Manning, Suvir Mirchandani, Eric Mitchell, Zanele Munyikwa, Suraj Nair, Avanika Narayan, Deepak Narayanan, Ben Newman, Allen Nie, Juan Carlos Niebles, Hamed Nilforoshan, Julian Nyarko, Giray Ogut, Laurel Orr, Isabel Papadimitriou, Joon Sung Park, Chris Piech, Eva Portelance, Christopher Potts, Aditi Raghunathan, Rob Reich, Hongyu Ren, Frieda Rong, Yusuf Roohani, Camilo Ruiz, Jack Ryan, Christopher Ré, Dorsa Sadigh, Shiori Sagawa, Keshav Santhanam, Andy Shih, Krishnan Srinivasan, Alex Tamkin, Rohan Taori, Armin W. Thomas, Florian Tramèr, Rose E. Wang, William Wang, Bohan Wu, Jiajun Wu, Yuhuai Wu, Sang Michael Xie, Michihiro Yasunaga, Jiaxuan You, Matei Zaharia, Michael Zhang, Tianyi Zhang, Xikun Zhang, Yuhui Zhang, Lucia Zheng, Kaitlyn Zhou, Percy Liang

* Authored by the Center for Research on Foundation Models (CRFM) at the Stanford Institute for Human-Centered Artificial Intelligence (HAI) 

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Personalized Federated Learning with First Order Model Optimization


Jan 28, 2021
Michael Zhang, Karan Sapra, Sanja Fidler, Serena Yeung, Jose M. Alvarez

* ICLR 2021 

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Using Computer Vision to Automate Hand Detection and Tracking of Surgeon Movements in Videos of Open Surgery


Dec 13, 2020
Michael Zhang, Xiaotian Cheng, Daniel Copeland, Arjun Desai, Melody Y. Guan, Gabriel A. Brat, Serena Yeung

* AMIA 2020 Annual Symposium 

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Characterizing Policy Divergence for Personalized Meta-Reinforcement Learning


Oct 09, 2020
Michael Zhang

* Deep Reinforcement Learning Workshop, NeurIPS 2019; Workshop on Meta-Learning (Meta-Learn), NeurIPS 2019 

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Soft Multicopter Control using Neural Dynamics Identification


Sep 02, 2020
Yitong Deng, Yaorui Zhang, Xingzhe He, Shuqi Yang, Yunjin Tong, Michael Zhang, Daniel DiPietro, Bo Zhu


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Patient-Specific Effects of Medication Using Latent Force Models with Gaussian Processes


Jun 01, 2019
Li-Fang Cheng, Bianca Dumitrascu, Michael Zhang, Corey Chivers, Michael Draugelis, Kai Li, Barbara E. Engelhardt


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Deep Weighted Averaging Classifiers


Nov 18, 2018
Dallas Card, Michael Zhang, Noah A. Smith

* 13 pages, 8 figures, 5 tables, added DOI and updated to meet ACM formatting requirements, In Proceedings of FAT* (2019) 

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Reverse Curriculum Generation for Reinforcement Learning


Jul 23, 2018
Carlos Florensa, David Held, Markus Wulfmeier, Michael Zhang, Pieter Abbeel

* Published at the 1st Conference on Robot Learning (CoRL 2017) 

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Probabilistically Safe Policy Transfer


May 15, 2017
David Held, Zoe McCarthy, Michael Zhang, Fred Shentu, Pieter Abbeel


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