Gradient Descent Provably Optimizes Over-parameterized Neural Networks

4 October 2018

Aarti Singh

Papers citing "Gradient Descent Provably Optimizes Over-parameterized Neural Networks"

50 / 244 papers shown

Title
Generalized Gradient Flows with Provable Fixed-Time Convergence and Fast Evasion of Non-Degenerate Saddle Points Mayank Baranwal Param Budhraja V. Raj A. Hota 23 2 0 07 Dec 2022
Infinite-width limit of deep linear neural networks Lénaïc Chizat Maria Colombo Xavier Fernández-Real Alessio Figalli 31 14 0 29 Nov 2022
Bypass Exponential Time Preprocessing: Fast Neural Network Training via Weight-Data Correlation Preprocessing Josh Alman Jiehao Liang Zhao-quan Song Ruizhe Zhang Danyang Zhuo 71 31 0 25 Nov 2022
Characterizing the Spectrum of the NTK via a Power Series Expansion Michael Murray Hui Jin Benjamin Bowman Guido Montúfar 30 11 0 15 Nov 2022
LOFT: Finding Lottery Tickets through Filter-wise Training Qihan Wang Chen Dun Fangshuo Liao C. Jermaine Anastasios Kyrillidis 18 3 0 28 Oct 2022
Global Convergence of SGD On Two Layer Neural Nets Pulkit Gopalani Anirbit Mukherjee 18 5 0 20 Oct 2022
Theoretical Guarantees for Permutation-Equivariant Quantum Neural Networks Louis Schatzki Martín Larocca Quynh T. Nguyen F. Sauvage M. Cerezo 27 84 0 18 Oct 2022
From Gradient Flow on Population Loss to Learning with Stochastic Gradient Descent Satyen Kale Jason D. Lee Chris De Sa Ayush Sekhari Karthik Sridharan 21 4 0 13 Oct 2022
What Can the Neural Tangent Kernel Tell Us About Adversarial Robustness? Nikolaos Tsilivis Julia Kempe AAML 39 16 0 11 Oct 2022
Efficient NTK using Dimensionality Reduction Nir Ailon Supratim Shit 26 0 0 10 Oct 2022
Dynamical Isometry for Residual Networks Advait Gadhikar R. Burkholz ODL AI4CE 32 2 0 05 Oct 2022
On the optimization and generalization of overparameterized implicit neural networks Tianxiang Gao Hongyang Gao MLT AI4CE 19 3 0 30 Sep 2022
Lazy vs hasty: linearization in deep networks impacts learning schedule based on example difficulty Thomas George Guillaume Lajoie A. Baratin 23 5 0 19 Sep 2022
Approximation results for Gradient Descent trained Shallow Neural Networks in $1d$ R. Gentile G. Welper ODL 44 6 0 17 Sep 2022
Robustness in deep learning: The good (width), the bad (depth), and the ugly (initialization) Zhenyu Zhu Fanghui Liu Grigorios G. Chrysos V. Cevher 39 19 0 15 Sep 2022
Towards Understanding Mixture of Experts in Deep Learning Zixiang Chen Yihe Deng Yue-bo Wu Quanquan Gu Yuan-Fang Li MLT MoE 27 53 0 04 Aug 2022
Analyzing Sharpness along GD Trajectory: Progressive Sharpening and Edge of Stability Z. Li Zixuan Wang Jian Li 19 42 0 26 Jul 2022
Hidden Progress in Deep Learning: SGD Learns Parities Near the Computational Limit Boaz Barak Benjamin L. Edelman Surbhi Goel Sham Kakade Eran Malach Cyril Zhang 25 123 0 18 Jul 2022
Efficient Augmentation for Imbalanced Deep Learning Damien Dablain C. Bellinger Bartosz Krawczyk Nitesh V. Chawla 22 7 0 13 Jul 2022
Implicit Bias of Gradient Descent on Reparametrized Models: On Equivalence to Mirror Descent Zhiyuan Li Tianhao Wang Jason D. Lee Sanjeev Arora 32 27 0 08 Jul 2022
Neural Networks can Learn Representations with Gradient Descent Alexandru Damian Jason D. Lee Mahdi Soltanolkotabi SSL MLT 17 112 0 30 Jun 2022
Bounding the Width of Neural Networks via Coupled Initialization -- A Worst Case Analysis Alexander Munteanu Simon Omlor Zhao-quan Song David P. Woodruff 25 15 0 26 Jun 2022
Learning sparse features can lead to overfitting in neural networks Leonardo Petrini Francesco Cagnetta Eric Vanden-Eijnden M. Wyart MLT 29 23 0 24 Jun 2022
Large-width asymptotics for ReLU neural networks with $α$ -Stable initializations Stefano Favaro S. Fortini Stefano Peluchetti 20 2 0 16 Jun 2022
Why Quantization Improves Generalization: NTK of Binary Weight Neural Networks Kaiqi Zhang Ming Yin Yu-Xiang Wang MQ 16 4 0 13 Jun 2022
On the Convergence to a Global Solution of Shuffling-Type Gradient Algorithms Lam M. Nguyen Trang H. Tran 32 2 0 13 Jun 2022
Neural Collapse: A Review on Modelling Principles and Generalization Vignesh Kothapalli 21 71 0 08 Jun 2022
Identifying good directions to escape the NTK regime and efficiently learn low-degree plus sparse polynomials Eshaan Nichani Yunzhi Bai Jason D. Lee 21 10 0 08 Jun 2022
Non-convex online learning via algorithmic equivalence Udaya Ghai Zhou Lu Elad Hazan 14 8 0 30 May 2022
Global Convergence of Over-parameterized Deep Equilibrium Models Zenan Ling Xingyu Xie Qiuhao Wang Zongpeng Zhang Zhouchen Lin 27 12 0 27 May 2022
Empirical Phase Diagram for Three-layer Neural Networks with Infinite Width Hanxu Zhou Qixuan Zhou Zhenyuan Jin Tao Luo Yaoyu Zhang Zhi-Qin John Xu 22 20 0 24 May 2022
Transition to Linearity of General Neural Networks with Directed Acyclic Graph Architecture Libin Zhu Chaoyue Liu M. Belkin GNN AI4CE 15 4 0 24 May 2022
On the Effective Number of Linear Regions in Shallow Univariate ReLU Networks: Convergence Guarantees and Implicit Bias Itay Safran Gal Vardi Jason D. Lee MLT 51 23 0 18 May 2022
Trading Positional Complexity vs. Deepness in Coordinate Networks Jianqiao Zheng Sameera Ramasinghe Xueqian Li Simon Lucey 23 18 0 18 May 2022
High-dimensional Asymptotics of Feature Learning: How One Gradient Step Improves the Representation Jimmy Ba Murat A. Erdogdu Taiji Suzuki Zhichao Wang Denny Wu Greg Yang MLT 29 121 0 03 May 2022
Dynamic Programming in Rank Space: Scaling Structured Inference with Low-Rank HMMs and PCFGs Songlin Yang Wei Liu Kewei Tu 13 8 0 01 May 2022
Beyond the Quadratic Approximation: the Multiscale Structure of Neural Network Loss Landscapes Chao Ma D. Kunin Lei Wu Lexing Ying 25 27 0 24 Apr 2022
Theory of Graph Neural Networks: Representation and Learning Stefanie Jegelka GNN AI4CE 33 68 0 16 Apr 2022
On Convergence Lemma and Convergence Stability for Piecewise Analytic Functions Xiaotie Deng Hanyu Li Ningyuan Li 8 0 0 04 Apr 2022
Convergence of gradient descent for deep neural networks S. Chatterjee ODL 19 20 0 30 Mar 2022
On the (Non-)Robustness of Two-Layer Neural Networks in Different Learning Regimes Elvis Dohmatob A. Bietti AAML 21 13 0 22 Mar 2022
The Spectral Bias of Polynomial Neural Networks Moulik Choraria L. Dadi Grigorios G. Chrysos Julien Mairal V. Cevher 22 18 0 27 Feb 2022
Sparse Neural Additive Model: Interpretable Deep Learning with Feature Selection via Group Sparsity Shiyun Xu Zhiqi Bu Pratik Chaudhari Ian J. Barnett 19 21 0 25 Feb 2022
Random Feature Amplification: Feature Learning and Generalization in Neural Networks Spencer Frei Niladri S. Chatterji Peter L. Bartlett MLT 30 29 0 15 Feb 2022
Noise Regularizes Over-parameterized Rank One Matrix Recovery, Provably Tianyi Liu Yan Li Enlu Zhou Tuo Zhao 38 1 0 07 Feb 2022
Demystify Optimization and Generalization of Over-parameterized PAC-Bayesian Learning Wei Huang Chunrui Liu Yilan Chen Tianyu Liu R. Xu BDL MLT 19 2 0 04 Feb 2022
Improved Overparametrization Bounds for Global Convergence of Stochastic Gradient Descent for Shallow Neural Networks Bartlomiej Polaczyk J. Cyranka ODL 28 3 0 28 Jan 2022
How does unlabeled data improve generalization in self-training? A one-hidden-layer theoretical analysis Shuai Zhang M. Wang Sijia Liu Pin-Yu Chen Jinjun Xiong SSL MLT 39 22 0 21 Jan 2022
Implicit Bias of MSE Gradient Optimization in Underparameterized Neural Networks Benjamin Bowman Guido Montúfar 18 11 0 12 Jan 2022
Rethinking Influence Functions of Neural Networks in the Over-parameterized Regime Rui Zhang Shihua Zhang TDI 19 21 0 15 Dec 2021