Fine-Grained Analysis of Optimization and Generalization for Overparameterized Two-Layer Neural Networks

24 January 2019

Papers citing "Fine-Grained Analysis of Optimization and Generalization for Overparameterized Two-Layer Neural Networks"

50 / 239 papers shown

Title
Neural Multivariate Regression: Qualitative Insights from the Unconstrained Feature Model George Andriopoulos Soyuj Jung Basnet Juan Guevara Li Guo Keith Ross 30 0 0 14 May 2025
Mallows-type model averaging: Non-asymptotic analysis and all-subset combination Jingfu Peng MoMe 37 0 0 05 May 2025
A Comprehensive Survey of Synthetic Tabular Data Generation Ruxue Shi Yili Wang Mengnan Du Xu Shen Xin Wang 49 2 0 23 Apr 2025
Explainable Neural Networks with Guarantees: A Sparse Estimation Approach Antoine Ledent Peng Liu FAtt 109 0 0 20 Feb 2025
Feature Learning Beyond the Edge of Stability Dávid Terjék MLT 46 0 0 18 Feb 2025
SNeRV: Spectra-preserving Neural Representation for Video Jina Kim Jihoo Lee Je-Won Kang 43 3 0 03 Jan 2025
Variance-Aware Linear UCB with Deep Representation for Neural Contextual Bandits H. Bui Enrique Mallada Anqi Liu 144 0 0 08 Nov 2024
Towards Understanding Why FixMatch Generalizes Better Than Supervised Learning Jingyang Li Jiachun Pan Vincent Y. F. Tan Kim-Chuan Toh Pan Zhou AAML MLT 48 0 0 15 Oct 2024
Adversarial Training Can Provably Improve Robustness: Theoretical Analysis of Feature Learning Process Under Structured Data Binghui Li Yuanzhi Li OOD 33 2 0 11 Oct 2024
Extended convexity and smoothness and their applications in deep learning Binchuan Qi Wei Gong Li Li 63 0 0 08 Oct 2024
Tuning Frequency Bias of State Space Models Annan Yu Dongwei Lyu S. H. Lim Michael W. Mahoney N. Benjamin Erichson 47 3 0 02 Oct 2024
Optimal Kernel Quantile Learning with Random Features Caixing Wang Xingdong Feng 51 0 0 24 Aug 2024
Many Perception Tasks are Highly Redundant Functions of their Input Data Rahul Ramesh Anthony Bisulco Ronald W. DiTullio Linran Wei Vijay Balasubramanian Kostas Daniilidis Pratik Chaudhari 44 2 0 18 Jul 2024
Loss Gradient Gaussian Width based Generalization and Optimization Guarantees A. Banerjee Qiaobo Li Yingxue Zhou 52 0 0 11 Jun 2024
On the Rashomon ratio of infinite hypothesis sets Evzenie Coupkova Mireille Boutin 37 1 0 27 Apr 2024
$Implicit Bias of AdamW: $\ell_\infty$ Norm Constrained Optimization$ Implicit Bias of AdamW: $\ell_\infty$ Norm Constrained Optimization Shuo Xie Zhiyuan Li OffRL 50 13 0 05 Apr 2024
Grounding and Enhancing Grid-based Models for Neural Fields Zelin Zhao Fenglei Fan Wenlong Liao Junchi Yan 39 5 0 29 Mar 2024
NTK-Guided Few-Shot Class Incremental Learning Jingren Liu Zhong Ji Yanwei Pang YunLong Yu CLL 42 3 0 19 Mar 2024
$How does promoting the minority fraction affect generalization? A theoretical study of the one-hidden-layer neural network on group imbalance$ How does promoting the minority fraction affect generalization? A theoretical study of the one-hidden-layer neural network on group imbalance Hongkang Li Shuai Zhang Yihua Zhang Meng Wang Sijia Liu Pin-Yu Chen 41 4 0 12 Mar 2024
Loss Landscape of Shallow ReLU-like Neural Networks: Stationary Points, Saddle Escape, and Network Embedding Zhengqing Wu Berfin Simsek Francois Ged ODL 48 0 0 08 Feb 2024
Non-convergence to global minimizers for Adam and stochastic gradient descent optimization and constructions of local minimizers in the training of artificial neural networks Arnulf Jentzen Adrian Riekert 38 4 0 07 Feb 2024
Characterizing Overfitting in Kernel Ridgeless Regression Through the Eigenspectrum Tin Sum Cheng Aurelien Lucchi Anastasis Kratsios David Belius 40 8 0 02 Feb 2024
$\emph{Lifted} RDT based capacity analysis of the 1-hidden layer treelike \emph{sign} perceptrons neural networks$ \emph{Lifted} RDT based capacity analysis of the 1-hidden layer treelike \emph{sign} perceptrons neural networks M. Stojnic 27 1 0 13 Dec 2023
Capacity of the treelike sign perceptrons neural networks with one hidden layer -- RDT based upper bounds M. Stojnic 21 4 0 13 Dec 2023
Gradual Domain Adaptation: Theory and Algorithms Yifei He Haoxiang Wang Bo Li Han Zhao CLL 52 6 0 20 Oct 2023
Gradient constrained sharpness-aware prompt learning for vision-language models Liangchen Liu Nannan Wang Dawei Zhou Xinbo Gao Decheng Liu Xi Yang Tongliang Liu VLM 33 2 0 14 Sep 2023
How to Protect Copyright Data in Optimization of Large Language Models? T. Chu Zhao Song Chiwun Yang 40 29 0 23 Aug 2023
Understanding Deep Neural Networks via Linear Separability of Hidden Layers Chao Zhang Xinyuan Chen Wensheng Li Lixue Liu Wei Wu Dacheng Tao 28 3 0 26 Jul 2023
Efficient SGD Neural Network Training via Sublinear Activated Neuron Identification Lianke Qin Zhao Song Yuanyuan Yang 25 9 0 13 Jul 2023
Training-Free Neural Active Learning with Initialization-Robustness Guarantees Apivich Hemachandra Zhongxiang Dai Jasraj Singh See-Kiong Ng K. H. Low AAML 36 6 0 07 Jun 2023
Generalization Guarantees of Gradient Descent for Multi-Layer Neural Networks Puyu Wang Yunwen Lei Di Wang Yiming Ying Ding-Xuan Zhou MLT 29 4 0 26 May 2023
Fast Convergence in Learning Two-Layer Neural Networks with Separable Data Hossein Taheri Christos Thrampoulidis MLT 16 3 0 22 May 2023
Tight conditions for when the NTK approximation is valid Enric Boix-Adserà Etai Littwin 30 0 0 22 May 2023
Provable Guarantees for Nonlinear Feature Learning in Three-Layer Neural Networks Eshaan Nichani Alexandru Damian Jason D. Lee MLT 44 13 0 11 May 2023
On the Eigenvalue Decay Rates of a Class of Neural-Network Related Kernel Functions Defined on General Domains Yicheng Li Zixiong Yu Y. Cotronis Qian Lin 55 13 0 04 May 2023
Wide neural networks: From non-gaussian random fields at initialization to the NTK geometry of training Luís Carvalho Joao L. Costa José Mourao Gonccalo Oliveira AI4CE 26 1 0 06 Apr 2023
On the Stepwise Nature of Self-Supervised Learning James B. Simon Maksis Knutins Liu Ziyin Daniel Geisz Abraham J. Fetterman Joshua Albrecht SSL 37 30 0 27 Mar 2023
Online Learning for the Random Feature Model in the Student-Teacher Framework Roman Worschech B. Rosenow 46 0 0 24 Mar 2023
Learning Fractals by Gradient Descent Cheng-Hao Tu Hong-You Chen David Carlyn Wei-Lun Chao 23 2 0 14 Mar 2023
Over-Parameterization Exponentially Slows Down Gradient Descent for Learning a Single Neuron Weihang Xu S. Du 37 16 0 20 Feb 2023
Reinforcement Learning with Function Approximation: From Linear to Nonlinear Jihao Long Jiequn Han 27 5 0 20 Feb 2023
A Theoretical Understanding of Shallow Vision Transformers: Learning, Generalization, and Sample Complexity Hongkang Li Hao Wu Sijia Liu Pin-Yu Chen ViT MLT 37 57 0 12 Feb 2023
Beyond the Universal Law of Robustness: Sharper Laws for Random Features and Neural Tangent Kernels Simone Bombari Shayan Kiyani Marco Mondelli AAML 40 10 0 03 Feb 2023
Over-parameterised Shallow Neural Networks with Asymmetrical Node Scaling: Global Convergence Guarantees and Feature Learning François Caron Fadhel Ayed Paul Jung Hoileong Lee Juho Lee Hongseok Yang 64 2 0 02 Feb 2023
Width and Depth Limits Commute in Residual Networks Soufiane Hayou Greg Yang 44 14 0 01 Feb 2023
Supervision Complexity and its Role in Knowledge Distillation Hrayr Harutyunyan A. S. Rawat A. Menon Seungyeon Kim Surinder Kumar 30 12 0 28 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