Escaping From Saddle Points --- Online Stochastic Gradient for Tensor Decomposition

6 March 2015

Furong Huang

Papers citing "Escaping From Saddle Points --- Online Stochastic Gradient for Tensor Decomposition"

50 / 211 papers shown

Title
Dyn-D $^2$ P: Dynamic Differentially Private Decentralized Learning with Provable Utility Guarantee Zehan Zhu Yan Huang Xin Wang Shouling Ji Jinming Xu 26 0 0 10 May 2025
Preconditioned Gradient Descent for Over-Parameterized Nonconvex Matrix Factorization G. Zhang S. Fattahi Richard Y. Zhang 45 36 0 13 Apr 2025
A Piecewise Lyapunov Analysis of Sub-quadratic SGD: Applications to Robust and Quantile Regression Yixuan Zhang Dongyan Yudong Chen Qiaomin Xie 36 0 0 11 Apr 2025
Tensor Methods in High Dimensional Data Analysis: Opportunities and Challenges Arnab Auddy Dong Xia Ming Yuan AI4CE 50 2 0 28 May 2024
Training-set-free two-stage deep learning for spectroscopic data de-noising Dongchen Huang Junde Liu Tian Qian Hongming Weng 36 0 0 29 Feb 2024
High Probability Guarantees for Random Reshuffling Hengxu Yu Xiao Li 45 2 0 20 Nov 2023
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
Provably Accelerating Ill-Conditioned Low-rank Estimation via Scaled Gradient Descent, Even with Overparameterization Cong Ma Xingyu Xu Tian Tong Yuejie Chi 18 9 0 09 Oct 2023
Symmetry & Critical Points for Symmetric Tensor Decomposition Problems Yossi Arjevani Gal Vinograd 31 5 0 13 Jun 2023
Correlated Noise in Epoch-Based Stochastic Gradient Descent: Implications for Weight Variances Marcel Kühn B. Rosenow 19 3 0 08 Jun 2023
How to escape sharp minima with random perturbations Kwangjun Ahn Ali Jadbabaie S. Sra ODL 34 6 0 25 May 2023
Convergence of Alternating Gradient Descent for Matrix Factorization R. Ward T. Kolda 22 6 0 11 May 2023
Convex Dual Theory Analysis of Two-Layer Convolutional Neural Networks with Soft-Thresholding Chunyan Xiong Meng Lu Xiaotong Yu JIAN-PENG Cao Zhong Chen D. Guo X. Qu MLT 40 0 0 14 Apr 2023
AGAD: Adversarial Generative Anomaly Detection Jian Shi Ni Zhang 21 0 0 09 Apr 2023
Type-II Saddles and Probabilistic Stability of Stochastic Gradient Descent Liu Ziyin Botao Li Tomer Galanti Masakuni Ueda 37 7 0 23 Mar 2023
Private (Stochastic) Non-Convex Optimization Revisited: Second-Order Stationary Points and Excess Risks Arun Ganesh Daogao Liu Sewoong Oh Abhradeep Thakurta ODL 27 12 0 20 Feb 2023
Almost Sure Saddle Avoidance of Stochastic Gradient Methods without the Bounded Gradient Assumption Jun Liu Ye Yuan ODL 19 1 0 15 Feb 2023
Understanding Incremental Learning of Gradient Descent: A Fine-grained Analysis of Matrix Sensing Jikai Jin Zhiyuan Li Kaifeng Lyu S. Du Jason D. Lee MLT 54 34 0 27 Jan 2023
An SDE for Modeling SAM: Theory and Insights Enea Monzio Compagnoni Luca Biggio Antonio Orvieto F. Proske Hans Kersting Aurelien Lucchi 25 13 0 19 Jan 2023
Escaping Saddle Points for Effective Generalization on Class-Imbalanced Data Harsh Rangwani Sumukh K Aithal Mayank Mishra R. Venkatesh Babu 31 29 0 28 Dec 2022
Gradient Descent-Type Methods: Background and Simple Unified Convergence Analysis Quoc Tran-Dinh Marten van Dijk 34 0 0 19 Dec 2022
Decentralized Nonconvex Optimization with Guaranteed Privacy and Accuracy Yongqiang Wang Tamer Basar 24 21 0 14 Dec 2022
A Novel Stochastic Gradient Descent Algorithm for Learning Principal Subspaces Charline Le Lan Joshua Greaves Jesse Farebrother Mark Rowland Fabian Pedregosa Rishabh Agarwal Marc G. Bellemare 52 8 0 08 Dec 2022
Generalized Gradient Flows with Provable Fixed-Time Convergence and Fast Evasion of Non-Degenerate Saddle Points Mayank Baranwal Param Budhraja V. Raj A. Hota 33 2 0 07 Dec 2022
Adap DP-FL: Differentially Private Federated Learning with Adaptive Noise Jie Fu Zhili Chen Xiao Han FedML 25 28 0 29 Nov 2022
Data-Adaptive Discriminative Feature Localization with Statistically Guaranteed Interpretation Ben Dai Xiaotong Shen Lingzhi Chen Chunlin Li Wei Pan FAtt 21 1 0 18 Nov 2022
Escaping From Saddle Points Using Asynchronous Coordinate Gradient Descent Marco Bornstein Jin-Peng Liu Jingling Li Furong Huang 21 0 0 17 Nov 2022
Passage-Mask: A Learnable Regularization Strategy for Retriever-Reader Models Shujian Zhang Chengyue Gong Xingchao Liu RALM 49 6 0 02 Nov 2022
Learning Single-Index Models with Shallow Neural Networks A. Bietti Joan Bruna Clayton Sanford M. Song 170 68 0 27 Oct 2022
Networked Signal and Information Processing Stefan Vlaski S. Kar Ali H. Sayed José M. F. Moura 49 16 0 25 Oct 2022
The Dynamics of Sharpness-Aware Minimization: Bouncing Across Ravines and Drifting Towards Wide Minima Peter L. Bartlett Philip M. Long Olivier Bousquet 76 34 0 04 Oct 2022
Zeroth-Order Negative Curvature Finding: Escaping Saddle Points without Gradients Hualin Zhang Huan Xiong Bin Gu 35 7 0 04 Oct 2022
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
Nonconvex Matrix Factorization is Geodesically Convex: Global Landscape Analysis for Fixed-rank Matrix Optimization From a Riemannian Perspective Yuetian Luo Nicolas García Trillos 24 6 0 29 Sep 2022
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 Can Yaras Peng Wang Zhihui Zhu Laura Balzano Qing Qu 25 42 0 19 Sep 2022
Gradient-Free Methods for Deterministic and Stochastic Nonsmooth Nonconvex Optimization Tianyi Lin Zeyu Zheng Michael I. Jordan 59 52 0 12 Sep 2022
Implicit Full Waveform Inversion with Deep Neural Representation Jian Sun K. Innanen AI4CE 40 32 0 08 Sep 2022
On the generalization of learning algorithms that do not converge N. Chandramoorthy Andreas Loukas Khashayar Gatmiry Stefanie Jegelka MLT 19 11 0 16 Aug 2022
A Gradient Smoothed Functional Algorithm with Truncated Cauchy Random Perturbations for Stochastic Optimization Akash Mondal A. PrashanthL. S. Bhatnagar 19 2 0 30 Jul 2022
High-dimensional limit theorems for SGD: Effective dynamics and critical scaling Gerard Ben Arous Reza Gheissari Aukosh Jagannath 62 58 0 08 Jun 2022
Preconditioned Gradient Descent for Overparameterized Nonconvex Burer--Monteiro Factorization with Global Optimality Certification G. Zhang S. Fattahi Richard Y. Zhang 59 23 0 07 Jun 2022
Uniform Generalization Bound on Time and Inverse Temperature for Gradient Descent Algorithm and its Application to Analysis of Simulated Annealing Keisuke Suzuki AI4CE 33 0 0 25 May 2022
Weak Convergence of Approximate reflection coupling and its Application to Non-convex Optimization Keisuke Suzuki 32 5 0 24 May 2022
Estimation and Inference by Stochastic Optimization Jean-Jacques Forneron 30 5 0 06 May 2022
Randomized Policy Optimization for Optimal Stopping Xinyi Guan V. Mišić 19 2 0 25 Mar 2022
Leveraging Randomized Smoothing for Optimal Control of Nonsmooth Dynamical Systems Quentin Le Lidec Fabian Schramm Louis Montaut Cordelia Schmid Ivan Laptev Justin Carpentier 38 24 0 08 Mar 2022
A Robust Spectral Algorithm for Overcomplete Tensor Decomposition Samuel B. Hopkins T. Schramm Jonathan Shi 25 23 0 05 Mar 2022
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
Robust Training under Label Noise by Over-parameterization Sheng Liu Zhihui Zhu Qing Qu Chong You NoLa OOD 27 106 0 28 Feb 2022