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2007.06753
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From Symmetry to Geometry: Tractable Nonconvex Problems
14 July 2020
Yuqian Zhang
Qing Qu
John N. Wright
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Papers citing
"From Symmetry to Geometry: Tractable Nonconvex Problems"
34 / 34 papers shown
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Low solution rank of the matrix LASSO under RIP with consequences for rank-constrained algorithms
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On the Necessity of Metalearning: Learning Suitable Parameterizations for Learning Processes
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A randomized algorithm for nonconvex minimization with inexact evaluations and complexity guarantees
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Neural Collapse in Multi-label Learning with Pick-all-label Loss
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Learning with Noisy Labels Using Collaborative Sample Selection and Contrastive Semi-Supervised Learning
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Expand-and-Cluster: Parameter Recovery of Neural Networks
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Symmetries, flat minima, and the conserved quantities of gradient flow
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31 Oct 2022
Are All Losses Created Equal: A Neural Collapse Perspective
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Chong You
Xiao Li
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Zhihui Zhu
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On Quantum Speedups for Nonconvex Optimization via Quantum Tunneling Walks
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Yizhou Liu
Weijie J. Su
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Neural Collapse with Normalized Features: A Geometric Analysis over the Riemannian Manifold
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Convergence and Recovery Guarantees of the K-Subspaces Method for Subspace Clustering
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Huikang Liu
Anthony Man-Cho So
Laura Balzano
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On the Optimization Landscape of Neural Collapse under MSE Loss: Global Optimality with Unconstrained Features
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Xiao Li
Tian Ding
Chong You
Qing Qu
Zhihui Zhu
483
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02 Mar 2022
A Geometric Approach to
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Wei Qian
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Yuqian Zhang
297
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An Unconstrained Layer-Peeled Perspective on Neural Collapse
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Yiping Lu
Yiliang Zhang
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Weijie J. Su
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Rank Overspecified Robust Matrix Recovery: Subgradient Method and Exact Recovery
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Liwei Jiang
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Qing Qu
Zhihui Zhu
270
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Nonconvex Factorization and Manifold Formulations are Almost Equivalent in Low-rank Matrix Optimization
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Xudong Li
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383
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Unique sparse decomposition of low rank matrices
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A Geometric Analysis of Neural Collapse with Unconstrained Features
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Tianyu Ding
Jinxin Zhou
Xiao Li
Chong You
Jeremias Sulam
Qing Qu
358
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06 May 2021
Scaling and Scalability: Provable Nonconvex Low-Rank Tensor Estimation from Incomplete Measurements
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Tian Tong
Cong Ma
Ashley Prater-Bennette
Erin E. Tripp
Yuejie Chi
447
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29 Apr 2021
HePPCAT: Probabilistic PCA for Data with Heteroscedastic Noise
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David Hong
Kyle Gilman
Laura Balzano
Jeffrey A. Fessler
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10 Jan 2021
Spectral Methods for Data Science: A Statistical Perspective
Yuxin Chen
Yuejie Chi
Jianqing Fan
Cong Ma
696
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Recent Theoretical Advances in Non-Convex Optimization
Marina Danilova
Pavel Dvurechensky
Alexander Gasnikov
Eduard A. Gorbunov
Sergey Guminov
Dmitry Kamzolov
Innokentiy Shibaev
457
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11 Dec 2020
Learning Mixtures of Low-Rank Models
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H. Vincent Poor
Yuxin Chen
368
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23 Sep 2020
Convex and Nonconvex Optimization Are Both Minimax-Optimal for Noisy Blind Deconvolution under Random Designs
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Jianqing Fan
B. Wang
Yuling Yan
454
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Chong You
Zhihui Zhu
Qing Qu
Yi-An Ma
191
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Depth Descent Synchronization in
S
O
(
D
)
\mathrm{SO}(D)
SO
(
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)
International Journal of Computer Vision (IJCV), 2020
Tyler Maunu
Gilad Lerman
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346
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0
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Manifold Gradient Descent Solves Multi-Channel Sparse Blind Deconvolution Provably and Efficiently
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Yuejie Chi
489
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25 Nov 2019
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