Quanquan Gu
Assistant Professor
I am an Assistant Professor of Computer Science at UCLA. My research is in statistical machine learning, with a focus on developing and analyzing nonconvex optimization algorithms for machine learning to understand large-scale, dynamic, complex and heterogeneous data, and building the theoretical foundations of deep learning. I am leading the Statistical Machine Learning Lab. I received my Ph.D. degree in Computer Science from the University of Illinois at Urbana-Champaign in 2014.
Here is my latest CV.
News and Annoucement
Recent Research Highlight
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Provably Efficient Reinforcement Learning for Discounted MDPs with
Feature Mapping
Dongruo Zhou, Jiafan He and Quanquan Gu, arXiv:2006.13165, 2020.
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How Much Over-parameterization Is Sufficient to Learn Deep ReLU
Networks?
Zixiang Chen*, Yuan Cao*, Difan Zou* and Quanquan Gu, in Proc. of the 9th International Conference on Learning Representations (ICLR), 2021. [arXiv]
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A Generalized Neural Tangent Kernel Analysis for Two-layer Neural Networks
Zixiang Chen, Yuan Cao, Quanquan Gu and Tong Zhang, in Proc. of Advances in Neural Information Processing Systems (NeurIPS) 33, 2020. [arXiv]
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Generalization Bounds of Stochastic Gradient Descent for Wide and Deep Neural Networks
Yuan Cao and Quanquan Gu, in Proc. of Advances in Neural Information Processing Systems (NeurIPS) 32, Vancouver, Canada, 2019. Spotlight presentation [arXiv]
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An Improved Analysis of Training Over-parameterized Deep Neural Networks
Difan Zou and Quanquan Gu, in Proc. of Advances in Neural Information Processing Systems (NeurIPS) 32, Vancouver, Canada, 2019. [arXiv]
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Stochastic Gradient Descent Optimizes Over-parameterized Deep ReLU
Networks
Difan Zou*, Yuan Cao*, Dongruo Zhou and Quanquan Gu, Accepted by the Machine Learning Journal (MLJ), 2019. [arXiv]
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Lower Bounds for Smooth Nonconvex Finite-Sum Optimization
Dongruo Zhou and Quanquan Gu, in Proc. of the 36th International Conference on Machine Learning (ICML), Long Beach, CA, USA, 2019. [arXiv]
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Stochastic Nested Variance Reduction for Nonconvex Optimization
Dongruo Zhou, Pan Xu and Quanquan Gu, In Proc. of Advances in Neural Information Processing Systems (NeurIPS) 31, Montréal, Canada, 2018. Spotlight presentation [arXiv]
Recent Services
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Area Chair for ICML (2019, 2020, 2021), NeurIPS (2019), ICLR (2020, 2021), AAAI (2020, 2021), IJCAI (2021), AISTATS (2020, 2021)
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Senior Program Commitee Member for IJCAI (2019, 2020), ACML (2019)
Awards
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AWS Machine Learning Research Award, 2020
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Simons Berkeley Research Fellowship, 2019
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Adobe Data Science Research Award, 2018
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Salesforce Deep Learning Research Award, 2018
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NSF CAREER Award, 2017
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Yahoo! Academic Career Enhancement Award, 2015
Contact
Address: EVI 282, 404 Westwood Plaza, Los Angeles, CA 90095
Email: qgu at cs dot ucla dot edu
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