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A Regression Approach to Learning-Augmented Online Algorithms



Keerti Anand , Rong Ge , Amit Kumar , Debmalya Panigrahi


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Customizing ML Predictions for Online Algorithms



Keerti Anand , Rong Ge , Debmalya Panigrahi


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Online Algorithms with Multiple Predictions



Keerti Anand , Rong Ge , Amit Kumar , Debmalya Panigrahi


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Towards Understanding the Data Dependency of Mixup-style Training



Muthu Chidambaram , Xiang Wang , Yuzheng Hu , Chenwei Wu , Rong Ge

* 25 pages, 13 figures 

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Outlier-Robust Sparse Estimation via Non-Convex Optimization



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



Rong Ge , Yunwei Ren , Xiang Wang , Mo Zhou


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



Mo Zhou , Rong Ge , Chi Jin


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Beyond Lazy Training for Over-parameterized Tensor Decomposition



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

* NeurIPS 2020; the first two authors contribute equally 

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Dissecting Hessian: Understanding Common Structure of Hessian in Neural Networks



Yikai Wu , Xingyu Zhu , Chenwei Wu , Annie Wang , Rong Ge

* 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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