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Sampling is as easy as learning the score: theory for diffusion models with minimal data assumptions


Oct 04, 2022
Sitan Chen, Sinho Chewi, Jerry Li, Yuanzhi Li, Adil Salim, Anru R. Zhang

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* 30 pages 

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Self-supervised Denoising via Low-rank Tensor Approximated Convolutional Neural Network


Sep 26, 2022
Chenyin Gao, Shu Yang, Anru R. Zhang

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Tensor-on-Tensor Regression: Riemannian Optimization, Over-parameterization, Statistical-computational Gap, and Their Interplay


Jun 17, 2022
Yuetian Luo, Anru R. Zhang

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Learning Polynomial Transformations


Apr 08, 2022
Sitan Chen, Jerry Li, Yuanzhi Li, Anru R. Zhang

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* 121 pages, comments welcome 

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On Geometric Connections of Embedded and Quotient Geometries in Riemannian Fixed-rank Matrix Optimization


Oct 23, 2021
Yuetian Luo, Xudong Li, Anru R. Zhang

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Nonconvex Factorization and Manifold Formulations are Almost Equivalent in Low-rank Matrix Optimization


Aug 03, 2021
Yuetian Luo, Xudong Li, Anru R. Zhang

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Low-rank Tensor Estimation via Riemannian Gauss-Newton: Statistical Optimality and Second-Order Convergence


Apr 27, 2021
Yuetian Luo, Anru R. Zhang

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Inference for Low-rank Tensors -- No Need to Debias


Dec 29, 2020
Dong Xia, Anru R. Zhang, Yuchen Zhou

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