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Customizing ML Predictions for Online Algorithms


May 18, 2022
Keerti Anand, Rong Ge, Debmalya Panigrahi

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Online Algorithms with Multiple Predictions


May 08, 2022
Keerti Anand, Rong Ge, Amit Kumar, Debmalya Panigrahi

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Towards Understanding the Data Dependency of Mixup-style Training


Oct 14, 2021
Muthu Chidambaram, Xiang Wang, Yuzheng Hu, Chenwei Wu, Rong Ge

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* 25 pages, 13 figures 

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Outlier-Robust Sparse Estimation via Non-Convex Optimization


Sep 23, 2021
Yu Cheng, Ilias Diakonikolas, Daniel M. Kane, Rong Ge, Shivam Gupta, Mahdi Soltanolkotabi

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Understanding Deflation Process in Over-parametrized Tensor Decomposition


Jun 11, 2021
Rong Ge, Yunwei Ren, Xiang Wang, Mo Zhou

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A Local Convergence Theory for Mildly Over-Parameterized Two-Layer Neural Network


Feb 04, 2021
Mo Zhou, Rong Ge, Chi Jin

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Beyond Lazy Training for Over-parameterized Tensor Decomposition


Oct 22, 2020
Xiang Wang, Chenwei Wu, Jason D. Lee, Tengyu Ma, Rong Ge

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* NeurIPS 2020; the first two authors contribute equally 

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Dissecting Hessian: Understanding Common Structure of Hessian in Neural Networks


Oct 08, 2020
Yikai Wu, Xingyu Zhu, Chenwei Wu, Annie Wang, Rong Ge

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* 29 pages, 26 figures. Main text: 8 pages, 6 figures. First two authors have equal contribution and are in alphabetical order 

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Efficient sampling from the Bingham distribution


Sep 30, 2020
Rong Ge, Holden Lee, Jianfeng Lu, Andrej Risteski

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Guarantees for Tuning the Step Size using a Learning-to-Learn Approach


Jun 30, 2020
Xiang Wang, Shuai Yuan, Chenwei Wu, Rong Ge

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