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Rong Ge

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

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* 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

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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

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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