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From Symmetry to Geometry: Tractable Nonconvex Problems

From Symmetry to Geometry: Tractable Nonconvex Problems

14 July 2020
Yuqian Zhang
Qing Qu
John N. Wright
ArXivPDFHTML

Papers citing "From Symmetry to Geometry: Tractable Nonconvex Problems"

20 / 20 papers shown
Title
Compressible Dynamics in Deep Overparameterized Low-Rank Learning &
  Adaptation
Compressible Dynamics in Deep Overparameterized Low-Rank Learning & Adaptation
Can Yaras
Peng Wang
Laura Balzano
Qing Qu
AI4CE
37
13
0
06 Jun 2024
Neural Collapse in Multi-label Learning with Pick-all-label Loss
Neural Collapse in Multi-label Learning with Pick-all-label Loss
Pengyu Li
Xiao Li
Yutong Wang
Qing Qu
30
8
0
24 Oct 2023
Symmetries, flat minima, and the conserved quantities of gradient flow
Symmetries, flat minima, and the conserved quantities of gradient flow
Bo Zhao
I. Ganev
Robin Walters
Rose Yu
Nima Dehmamy
47
16
0
31 Oct 2022
Are All Losses Created Equal: A Neural Collapse Perspective
Are All Losses Created Equal: A Neural Collapse Perspective
Jinxin Zhou
Chong You
Xiao Li
Kangning Liu
Sheng Liu
Qing Qu
Zhihui Zhu
36
59
0
04 Oct 2022
On Quantum Speedups for Nonconvex Optimization via Quantum Tunneling
  Walks
On Quantum Speedups for Nonconvex Optimization via Quantum Tunneling Walks
Yizhou Liu
Weijie J. Su
Tongyang Li
30
18
0
29 Sep 2022
Neural Collapse with Normalized Features: A Geometric Analysis over the
  Riemannian Manifold
Neural Collapse with Normalized Features: A Geometric Analysis over the Riemannian Manifold
Can Yaras
Peng Wang
Zhihui Zhu
Laura Balzano
Qing Qu
25
42
0
19 Sep 2022
On the Optimization Landscape of Neural Collapse under MSE Loss: Global
  Optimality with Unconstrained Features
On the Optimization Landscape of Neural Collapse under MSE Loss: Global Optimality with Unconstrained Features
Jinxin Zhou
Xiao Li
Tian Ding
Chong You
Qing Qu
Zhihui Zhu
30
99
0
02 Mar 2022
An Unconstrained Layer-Peeled Perspective on Neural Collapse
An Unconstrained Layer-Peeled Perspective on Neural Collapse
Wenlong Ji
Yiping Lu
Yiliang Zhang
Zhun Deng
Weijie J. Su
135
83
0
06 Oct 2021
Rank Overspecified Robust Matrix Recovery: Subgradient Method and Exact
  Recovery
Rank Overspecified Robust Matrix Recovery: Subgradient Method and Exact Recovery
Lijun Ding
Liwei Jiang
Yudong Chen
Qing Qu
Zhihui Zhu
31
29
0
23 Sep 2021
Nonconvex Factorization and Manifold Formulations are Almost Equivalent
  in Low-rank Matrix Optimization
Nonconvex Factorization and Manifold Formulations are Almost Equivalent in Low-rank Matrix Optimization
Yuetian Luo
Xudong Li
Anru R. Zhang
33
9
0
03 Aug 2021
The loss landscape of deep linear neural networks: a second-order
  analysis
The loss landscape of deep linear neural networks: a second-order analysis
E. M. Achour
Franccois Malgouyres
Sébastien Gerchinovitz
ODL
24
9
0
28 Jul 2021
Unique sparse decomposition of low rank matrices
Unique sparse decomposition of low rank matrices
Dian Jin
Xin Bing
Yuqian Zhang
27
4
0
14 Jun 2021
A Geometric Analysis of Neural Collapse with Unconstrained Features
A Geometric Analysis of Neural Collapse with Unconstrained Features
Zhihui Zhu
Tianyu Ding
Jinxin Zhou
Xiao Li
Chong You
Jeremias Sulam
Qing Qu
27
194
0
06 May 2021
Exploring Deep Neural Networks via Layer-Peeled Model: Minority Collapse
  in Imbalanced Training
Exploring Deep Neural Networks via Layer-Peeled Model: Minority Collapse in Imbalanced Training
Cong Fang
Hangfeng He
Qi Long
Weijie J. Su
FAtt
130
167
0
29 Jan 2021
HePPCAT: Probabilistic PCA for Data with Heteroscedastic Noise
HePPCAT: Probabilistic PCA for Data with Heteroscedastic Noise
David Hong
Kyle Gilman
Laura Balzano
Jeffrey A. Fessler
40
19
0
10 Jan 2021
Spectral Methods for Data Science: A Statistical Perspective
Spectral Methods for Data Science: A Statistical Perspective
Yuxin Chen
Yuejie Chi
Jianqing Fan
Cong Ma
40
165
0
15 Dec 2020
Depth Descent Synchronization in $\mathrm{SO}(D)$
Depth Descent Synchronization in SO(D)\mathrm{SO}(D)SO(D)
Tyler Maunu
Gilad Lerman
MDE
37
2
0
13 Feb 2020
Manifold Gradient Descent Solves Multi-Channel Sparse Blind
  Deconvolution Provably and Efficiently
Manifold Gradient Descent Solves Multi-Channel Sparse Blind Deconvolution Provably and Efficiently
Laixi Shi
Yuejie Chi
30
26
0
25 Nov 2019
Global optimality conditions for deep neural networks
Global optimality conditions for deep neural networks
Chulhee Yun
S. Sra
Ali Jadbabaie
128
117
0
08 Jul 2017
Tensor Decomposition for Signal Processing and Machine Learning
Tensor Decomposition for Signal Processing and Machine Learning
N. Sidiropoulos
L. De Lathauwer
Xiao Fu
Kejun Huang
Evangelos E. Papalexakis
Christos Faloutsos
111
1,343
0
06 Jul 2016
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