Global Optimality in Tensor Factorization, Deep Learning, and Beyond

24 June 2015

Papers citing "Global Optimality in Tensor Factorization, Deep Learning, and Beyond"

50 / 83 papers shown

Title
Guarantees of a Preconditioned Subgradient Algorithm for Overparameterized Asymmetric Low-rank Matrix Recovery Paris Giampouras HanQin Cai René Vidal 143 4 0 22 Oct 2024
Simplicity within biological complexity Nataša Pržulj N. Malod-Dognin 68 0 0 15 May 2024
Differentially Private Adapters for Parameter Efficient Acoustic Modeling Chun-Wei Ho Chao-Han Huck Yang Sabato Marco Siniscalchi 98 1 0 19 May 2023
Are All Losses Created Equal: A Neural Collapse Perspective Jinxin Zhou Chong You Xiao Li Kangning Liu Sheng Liu Qing Qu Zhihui Zhu 76 65 0 04 Oct 2022
On the generalization of learning algorithms that do not converge N. Chandramoorthy Andreas Loukas Khashayar Gatmiry Stefanie Jegelka MLT 91 11 0 16 Aug 2022
Neural Collapse: A Review on Modelling Principles and Generalization Vignesh Kothapalli 158 82 0 08 Jun 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 78 102 0 02 Mar 2022
Low-Pass Filtering SGD for Recovering Flat Optima in the Deep Learning Optimization Landscape Devansh Bisla Jing Wang A. Choromańska 104 37 0 20 Jan 2022
Over-Parametrized Matrix Factorization in the Presence of Spurious Stationary Points Armin Eftekhari 50 1 0 25 Dec 2021
Error Bounds for a Matrix-Vector Product Approximation with Deep ReLU Neural Networks T. Getu 54 2 0 25 Nov 2021
An Unconstrained Layer-Peeled Perspective on Neural Collapse Wenlong Ji Yiping Lu Yiliang Zhang Zhun Deng Weijie J. Su 203 87 0 06 Oct 2021
Two-level monotonic multistage recommender systems Ben Dai Xiaotong Shen Wei Pan 47 1 0 06 Oct 2021
Tensor Methods in Computer Vision and Deep Learning Yannis Panagakis Jean Kossaifi Grigorios G. Chrysos James Oldfield M. Nicolaou Anima Anandkumar Stefanos Zafeiriou 62 126 0 07 Jul 2021
Understanding approximate and unrolled dictionary learning for pattern recovery Benoit Malézieux Thomas Moreau M. Kowalski MU 54 13 0 11 Jun 2021
Marginalizable Density Models D. Gilboa Ari Pakman Thibault Vatter BDL 65 5 0 08 Jun 2021
A Geometric Analysis of Neural Collapse with Unconstrained Features Zhihui Zhu Tianyu Ding Jinxin Zhou Xiao Li Chong You Jeremias Sulam Qing Qu 88 204 0 06 May 2021
Noether: The More Things Change, the More Stay the Same Grzegorz Gluch R. Urbanke 58 18 0 12 Apr 2021
Why Do Local Methods Solve Nonconvex Problems? Tengyu Ma 54 13 0 24 Mar 2021
The Nonconvex Geometry of Linear Inverse Problems Armin Eftekhari Peyman Mohajerin Esfahani 77 1 0 07 Jan 2021
Learning Graph Neural Networks with Approximate Gradient Descent Qunwei Li Shaofeng Zou Leon Wenliang Zhong GNN 93 1 0 07 Dec 2020
Escaping Saddle-Points Faster under Interpolation-like Conditions Abhishek Roy Krishnakumar Balasubramanian Saeed Ghadimi P. Mohapatra 67 1 0 28 Sep 2020
From Symmetry to Geometry: Tractable Nonconvex Problems Yuqian Zhang Qing Qu John N. Wright 87 45 0 14 Jul 2020
Optimization and Generalization of Shallow Neural Networks with Quadratic Activation Functions Stefano Sarao Mannelli Eric Vanden-Eijnden Lenka Zdeborová AI4CE 67 49 0 27 Jun 2020
The Hidden Convex Optimization Landscape of Two-Layer ReLU Neural Networks: an Exact Characterization of the Optimal Solutions Yifei Wang Jonathan Lacotte Mert Pilanci MLT 65 27 0 10 Jun 2020
Stationary Points of Shallow Neural Networks with Quadratic Activation Function D. Gamarnik Eren C. Kizildag Ilias Zadik 43 14 0 03 Dec 2019
How Much Over-parameterization Is Sufficient to Learn Deep ReLU Networks? Zixiang Chen Yuan Cao Difan Zou Quanquan Gu 77 123 0 27 Nov 2019
Beyond Linearization: On Quadratic and Higher-Order Approximation of Wide Neural Networks Yu Bai Jason D. Lee 65 116 0 03 Oct 2019
Stochastic Conditional Generative Networks with Basis Decomposition Ze Wang Xiuyuan Cheng Guillermo Sapiro Qiang Qiu GAN 135 18 0 25 Sep 2019
Why Learning of Large-Scale Neural Networks Behaves Like Convex Optimization Hui Jiang 21 8 0 06 Mar 2019
Generalization Error Bounds of Gradient Descent for Learning Over-parameterized Deep ReLU Networks Yuan Cao Quanquan Gu ODL MLT AI4CE 143 158 0 04 Feb 2019
Fine-Grained Analysis of Optimization and Generalization for Overparameterized Two-Layer Neural Networks Sanjeev Arora S. Du Wei Hu Zhiyuan Li Ruosong Wang MLT 234 974 0 24 Jan 2019
On the Benefit of Width for Neural Networks: Disappearance of Bad Basins Dawei Li Tian Ding Ruoyu Sun 116 38 0 28 Dec 2018
Deep Neural Network Concepts for Background Subtraction: A Systematic Review and Comparative Evaluation T. Bouwmans S. Javed M. Sultana Soon Ki Jung 84 322 0 13 Nov 2018
Gradient Descent Finds Global Minima of Deep Neural Networks S. Du Jason D. Lee Haochuan Li Liwei Wang Masayoshi Tomizuka ODL 283 1,136 0 09 Nov 2018
On the Convergence Rate of Training Recurrent Neural Networks Zeyuan Allen-Zhu Yuanzhi Li Zhao Song 242 193 0 29 Oct 2018
Benefits of over-parameterization with EM Ji Xu Daniel J. Hsu A. Maleki 287 31 0 26 Oct 2018
The loss surface of deep linear networks viewed through the algebraic geometry lens D. Mehta Tianran Chen Tingting Tang J. Hauenstein ODL 92 32 0 17 Oct 2018
Adaptive Low-Nonnegative-Rank Approximation for State Aggregation of Markov Chains Yaqi Duan Mengdi Wang Zaiwen Wen Ya-Xiang Yuan 28 7 0 14 Oct 2018
Regularization Matters: Generalization and Optimization of Neural Nets v.s. their Induced Kernel Colin Wei Jason D. Lee Qiang Liu Tengyu Ma 268 245 0 12 Oct 2018
Gradient Descent Provably Optimizes Over-parameterized Neural Networks S. Du Xiyu Zhai Barnabás Póczós Aarti Singh MLT ODL 272 1,276 0 04 Oct 2018
Global Optimality in Separable Dictionary Learning with Applications to the Analysis of Diffusion MRI Evan Schwab B. Haeffele René Vidal N. Charon OOD MedIm 42 2 0 15 Jul 2018
Algorithmic Regularization in Learning Deep Homogeneous Models: Layers are Automatically Balanced S. Du Wei Hu Jason D. Lee MLT 168 243 0 04 Jun 2018
Interpreting Deep Learning: The Machine Learning Rorschach Test? Adam S. Charles AAML HAI AI4CE 102 9 0 01 Jun 2018
Adding One Neuron Can Eliminate All Bad Local Minima Shiyu Liang Ruoyu Sun Jason D. Lee R. Srikant 100 90 0 22 May 2018
How Many Samples are Needed to Estimate a Convolutional or Recurrent Neural Network? S. Du Yining Wang Xiyu Zhai Sivaraman Balakrishnan Ruslan Salakhutdinov Aarti Singh SSL 91 57 0 21 May 2018
Improved Learning of One-hidden-layer Convolutional Neural Networks with Overlaps S. Du Surbhi Goel MLT 93 17 0 20 May 2018
The Loss Surface of XOR Artificial Neural Networks D. Mehta Xiaojun Zhao Edgar A. Bernal D. Wales 158 19 0 06 Apr 2018
Constrained Deep Learning using Conditional Gradient and Applications in Computer Vision Sathya Ravi Tuan Dinh Vishnu Suresh Lokhande Vikas Singh AI4CE 71 22 0 17 Mar 2018
On the Power of Over-parametrization in Neural Networks with Quadratic Activation S. Du Jason D. Lee 186 272 0 03 Mar 2018
Harnessing Structures in Big Data via Guaranteed Low-Rank Matrix Estimation Yudong Chen Yuejie Chi 147 172 0 23 Feb 2018