Yu Bai
Research
Preprints
Publications
Other technical reports
Talks
Near-Optimal Learning of Extensive-Form Games with Imperfect Information.
Learning and Games Program, Simons Institute, April 2022.
CISS Conference, Princeton University, March 2022.
Understanding the Under-Coverage Bias in Uncertainty Estimation.
Statistics Department Seminar, Rutgers University, October 2021.
Spotlight presentation at ICML 2021 Workshop on Distribution-free Uncertainty Quantification, July 2021.
ProxQuant: Quantized Neural Networks via Proximal Operators
ICLR, May 2019, New Orleans, LA.
Bytedance AI Lab, Dec 2018, Menlo Park, CA.
Amazon AI, Sep 2018, East Palo Alto, CA.
On the Generalization and Approximation in Generative Adversarial Networks (GANs)
ICLR, May 2019, New Orleans, LA.
Google Brain, Nov 2018, Mountain View, CA.
Salesforce Research, Nov 2018, Palo Alto, CA.
Stanford ML Seminar, Oct 2018, Stanford, CA.
Optimization Landscape of some Non-convex Learning Problems
Stanford Theory Seminar, Apr 2018, Stanford, CA.
Stanford ML Seminar, Apr 2017, Stanford, CA.
Service
Conference reviewing: NeurIPS (2018-2022), ICLR (2019-2023), ICML (2019-2021, 2023), COLT (2019-2020, 2022-2023), FOCS (2022), AIStats (2020), IEEE-ISIT (2018).
Journal reviewing: TMLR (Transactions of Machine Learning Research), The Annals of Statistics, JASA (Journal of the American Statistical Association), JRSS-B (Journal of the Royal Statistical Society: Series B), JMLR (Journal of Machine Learning Research), IEEE-TSP (Transactions on Signal Processing), SICON (SIAM Journal on
Control and Optimization).
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