Gradient Descent Provably Optimizes Over-parameterized Neural Networks

4 October 2018

Aarti Singh

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

50 / 302 papers shown

Title
CyclicFL: A Cyclic Model Pre-Training Approach to Efficient Federated Learning Peng Zhang Yingbo Zhou Ming Hu Xin Fu Xian Wei Mingsong Chen FedML 32 1 0 28 Jan 2023
A Simple Algorithm For Scaling Up Kernel Methods Tengyu Xu Bryan Kelly Semyon Malamud 16 0 0 26 Jan 2023
ZiCo: Zero-shot NAS via Inverse Coefficient of Variation on Gradients Guihong Li Yuedong Yang Kartikeya Bhardwaj R. Marculescu 36 61 0 26 Jan 2023
Convergence beyond the over-parameterized regime using Rayleigh quotients David A. R. Robin Kevin Scaman Marc Lelarge 27 3 0 19 Jan 2023
An Analysis of Attention via the Lens of Exchangeability and Latent Variable Models Yufeng Zhang Boyi Liu Qi Cai Lingxiao Wang Zhaoran Wang 53 11 0 30 Dec 2022
Learning Lipschitz Functions by GD-trained Shallow Overparameterized ReLU Neural Networks Ilja Kuzborskij Csaba Szepesvári 21 4 0 28 Dec 2022
COLT: Cyclic Overlapping Lottery Tickets for Faster Pruning of Convolutional Neural Networks Md. Ismail Hossain Mohammed Rakib M. M. L. Elahi Nabeel Mohammed Shafin Rahman 21 1 0 24 Dec 2022
Learning threshold neurons via the "edge of stability" Kwangjun Ahn Sébastien Bubeck Sinho Chewi Y. Lee Felipe Suarez Yi Zhang MLT 38 36 0 14 Dec 2022
Leveraging Unlabeled Data to Track Memorization Mahsa Forouzesh Hanie Sedghi Patrick Thiran NoLa TDI 34 4 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
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 Song Ruizhe Zhang Danyang Zhuo 77 31 0 25 Nov 2022
Mechanistic Mode Connectivity Ekdeep Singh Lubana Eric J. Bigelow Robert P. Dick David M. Krueger Hidenori Tanaka 32 45 0 15 Nov 2022
Characterizing the Spectrum of the NTK via a Power Series Expansion Michael Murray Hui Jin Benjamin Bowman Guido Montúfar 38 11 0 15 Nov 2022
A Functional-Space Mean-Field Theory of Partially-Trained Three-Layer Neural Networks Zhengdao Chen Eric Vanden-Eijnden Joan Bruna MLT 27 5 0 28 Oct 2022
LOFT: Finding Lottery Tickets through Filter-wise Training Qihan Wang Chen Dun Fangshuo Liao C. Jermaine Anastasios Kyrillidis 25 3 0 28 Oct 2022
Sparsity in Continuous-Depth Neural Networks H. Aliee Till Richter Mikhail Solonin I. Ibarra Fabian J. Theis Niki Kilbertus 29 10 0 26 Oct 2022
Global Convergence of SGD On Two Layer Neural Nets Pulkit Gopalani Anirbit Mukherjee 26 5 0 20 Oct 2022
Theoretical Guarantees for Permutation-Equivariant Quantum Neural Networks Louis Schatzki Martín Larocca Quynh T. Nguyen F. Sauvage M. Cerezo 39 85 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 27 4 0 13 Oct 2022
What Can the Neural Tangent Kernel Tell Us About Adversarial Robustness? Nikolaos Tsilivis Julia Kempe AAML 47 17 0 11 Oct 2022
Efficient NTK using Dimensionality Reduction Nir Ailon Supratim Shit 36 0 0 10 Oct 2022
On skip connections and normalisation layers in deep optimisation L. MacDonald Jack Valmadre Hemanth Saratchandran Simon Lucey ODL 19 1 0 10 Oct 2022
Dynamical Isometry for Residual Networks Advait Gadhikar R. Burkholz ODL AI4CE 40 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
Neural Networks Efficiently Learn Low-Dimensional Representations with SGD Alireza Mousavi-Hosseini Sejun Park M. Girotti Ioannis Mitliagkas Murat A. Erdogdu MLT 324 48 0 29 Sep 2022
Lazy vs hasty: linearization in deep networks impacts learning schedule based on example difficulty Thomas George Guillaume Lajoie A. Baratin 31 5 0 19 Sep 2022
Approximation results for Gradient Descent trained Shallow Neural Networks in $1d$ R. Gentile G. Welper ODL 54 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
Generalization Properties of NAS under Activation and Skip Connection Search Zhenyu Zhu Fanghui Liu Grigorios G. Chrysos V. Cevher AI4CE 28 15 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 30 53 0 04 Aug 2022
Analyzing Sharpness along GD Trajectory: Progressive Sharpening and Edge of Stability Z. Li Zixuan Wang Jian Li 19 44 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 39 123 0 18 Jul 2022
Efficient Augmentation for Imbalanced Deep Learning Damien Dablain C. Bellinger Bartosz Krawczyk Nitesh V. Chawla 32 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 42 27 0 08 Jul 2022
Neural Networks can Learn Representations with Gradient Descent Alexandru Damian Jason D. Lee Mahdi Soltanolkotabi SSL MLT 22 114 0 30 Jun 2022
Bounding the Width of Neural Networks via Coupled Initialization -- A Worst Case Analysis Alexander Munteanu Simon Omlor Zhao Song David P. Woodruff 30 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 42 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 24 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 25 74 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 29 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 32 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 25 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 23 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 59 23 0 18 May 2022
Trading Positional Complexity vs. Deepness in Coordinate Networks Jianqiao Zheng Sameera Ramasinghe Xueqian Li Simon Lucey 28 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 42 121 0 03 May 2022