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Gradient Descent Finds Global Minima of Deep Neural Networks

9 November 2018

Papers citing "Gradient Descent Finds Global Minima of Deep Neural Networks"

50 / 466 papers shown

Title
Joint Tensor-Train Parameterization for Efficient and Expressive Low-Rank Adaptation Jun Qi Chen-Yu Liu Sabato Marco Siniscalchi Chao-Han Huck Yang Min-hsiu Hsieh 15 0 0 19 Jun 2025
Generalization Bound of Gradient Flow through Training Trajectory and Data-dependent Kernel Yilan Chen Zhichao Wang Wei Huang Andi Han Taiji Suzuki Arya Mazumdar MLT 20 0 0 12 Jun 2025
Model Reprogramming Demystified: A Neural Tangent Kernel Perspective Ming-Yu Chung Jiashuo Fan Hancheng Ye Qinsi Wang Wei-Chen Shen Chia-Mu Yu Pin-Yu Chen Sy-Yen Kuo 24 1 0 31 May 2025
Querying Kernel Methods Suffices for Reconstructing their Training Data Daniel Barzilai Yuval Margalit Eitan Gronich Gilad Yehudai Meirav Galun Ronen Basri 35 0 0 25 May 2025
TULiP: Test-time Uncertainty Estimation via Linearization and Weight Perturbation Yuhui Zhang Dongshen Wu Yuichiro Wada Takafumi Kanamori OODD 241 1 0 22 May 2025
Training NTK to Generalize with KARE Johannes Schwab Bryan Kelly Semyon Malamud Teng Andrea Xu 146 0 0 16 May 2025
Divergence of Empirical Neural Tangent Kernel in Classification Problems Zixiong Yu Songtao Tian Guhan Chen 68 0 0 15 Apr 2025
On the Cone Effect in the Learning Dynamics Zhanpeng Zhou Yongyi Yang Jie Ren Mahito Sugiyama Junchi Yan 116 0 0 20 Mar 2025
Escaping from the Barren Plateau via Gaussian Initializations in Deep Variational Quantum Circuits Kaining Zhang Liu Liu Min-hsiu Hsieh Dacheng Tao 141 63 0 20 Feb 2025
Stability and Generalization in Free Adversarial Training Xiwei Cheng Kexin Fu Farzan Farnia AAML 84 3 0 08 Jan 2025
Multi-Label Bayesian Active Learning with Inter-Label Relationships Yuanyuan Qi Jueqing Lu Xiaohao Yang Joanne Enticott Lan Du 181 0 0 26 Nov 2024
Variance-Aware Linear UCB with Deep Representation for Neural Contextual Bandits H. Bui Enrique Mallada Anqi Liu 509 1 0 08 Nov 2024
Sharper Guarantees for Learning Neural Network Classifiers with Gradient Methods Hossein Taheri Christos Thrampoulidis Arya Mazumdar MLT 119 0 0 13 Oct 2024
Adversarial Training Can Provably Improve Robustness: Theoretical Analysis of Feature Learning Process Under Structured Data Binghui Li Yuanzhi Li OOD 94 4 0 11 Oct 2024
Extended convexity and smoothness and their applications in deep learning Binchuan Qi Wei Gong Li Li 107 0 0 08 Oct 2024
Measuring and Controlling Solution Degeneracy across Task-Trained Recurrent Neural Networks Ann Huang Satpreet H. Singh Flavio Martinelli Kanaka Rajan 96 0 0 04 Oct 2024
Simplicity bias and optimization threshold in two-layer ReLU networks Etienne Boursier Nicolas Flammarion 93 4 0 03 Oct 2024
From Lazy to Rich: Exact Learning Dynamics in Deep Linear Networks Clémentine Dominé Nicolas Anguita A. Proca Lukas Braun D. Kunin P. Mediano Andrew M. Saxe 131 6 0 22 Sep 2024
Monomial Matrix Group Equivariant Neural Functional Networks Hoang V. Tran Thieu N. Vo Tho H. Tran An T. Nguyen Tan M. Nguyen 140 9 0 18 Sep 2024
On the Pinsker bound of inner product kernel regression in large dimensions Weihao Lu Jialin Ding Haobo Zhang Qian Lin 93 1 0 02 Sep 2024
MAP: Low-compute Model Merging with Amortized Pareto Fronts via Quadratic Approximation Lu Li Tianze Zhang Zhiqi Bu Suyuchen Wang Huan He Jie Fu Yonghui Wu Jiang Bian Yong Chen Yoshua Bengio FedML MoMe 119 6 0 11 Jun 2024
Loss Gradient Gaussian Width based Generalization and Optimization Guarantees A. Banerjee Qiaobo Li Yingxue Zhou 158 0 0 11 Jun 2024
Reparameterization invariance in approximate Bayesian inference Hrittik Roy M. Miani Carl Henrik Ek Philipp Hennig Marvin Pfortner Lukas Tatzel Søren Hauberg BDL 119 9 0 05 Jun 2024
Approximation with Random Shallow ReLU Networks with Applications to Model Reference Adaptive Control Andrew G. Lamperski Tyler Lekang 53 3 0 25 Mar 2024
Non-asymptotic Analysis of Biased Adaptive Stochastic Approximation Sobihan Surendran Antoine Godichon-Baggioni Adeline Fermanian Sylvain Le Corff 109 2 0 05 Feb 2024
Critical Influence of Overparameterization on Sharpness-aware Minimization Sungbin Shin Dongyeop Lee Maksym Andriushchenko Namhoon Lee AAML 160 2 0 29 Nov 2023
Distributed Constrained Combinatorial Optimization leveraging Hypergraph Neural Networks Nasimeh Heydaribeni Xinrui Zhan Ruisi Zhang Tina Eliassi-Rad F. Koushanfar AI4CE 101 11 0 15 Nov 2023
Initialization Matters: Privacy-Utility Analysis of Overparameterized Neural Networks Jiayuan Ye Zhenyu Zhu Fanghui Liu Reza Shokri Volkan Cevher 87 13 0 31 Oct 2023
How Graph Neural Networks Learn: Lessons from Training Dynamics Chenxiao Yang Qitian Wu David Wipf Ruoyu Sun Junchi Yan AI4CE GNN 62 1 0 08 Oct 2023
Multilayer Multiset Neuronal Networks -- MMNNs Alexandre Benatti L. D. F. Costa 55 1 0 28 Aug 2023
Six Lectures on Linearized Neural Networks Theodor Misiakiewicz Andrea Montanari 134 13 0 25 Aug 2023
Quantifying the Optimization and Generalization Advantages of Graph Neural Networks Over Multilayer Perceptrons Wei Huang Yuanbin Cao Hong Wang Xin Cao Taiji Suzuki MLT 86 8 0 24 Jun 2023
Gradient is All You Need? Konstantin Riedl T. Klock Carina Geldhauser M. Fornasier 57 8 0 16 Jun 2023
Query Complexity of Active Learning for Function Family With Nearly Orthogonal Basis Xiangyi Chen Zhao Song Baochen Sun Junze Yin Danyang Zhuo 88 3 0 06 Jun 2023
Initial Guessing Bias: How Untrained Networks Favor Some Classes Emanuele Francazi Aurelien Lucchi Marco Baity-Jesi AI4CE 75 4 0 01 Jun 2023
Benign Overfitting in Deep Neural Networks under Lazy Training Zhenyu Zhu Fanghui Liu Grigorios G. Chrysos Francesco Locatello Volkan Cevher AI4CE 66 10 0 30 May 2023
An Analytic End-to-End Deep Learning Algorithm based on Collaborative Learning Sitan Li C. Cheah 47 1 0 26 May 2023
Scan and Snap: Understanding Training Dynamics and Token Composition in 1-layer Transformer Yuandong Tian Yiping Wang Beidi Chen S. Du MLT 109 79 0 25 May 2023
Fast Convergence in Learning Two-Layer Neural Networks with Separable Data Hossein Taheri Christos Thrampoulidis MLT 49 3 0 22 May 2023
Loss Spike in Training Neural Networks Zhongwang Zhang Z. Xu 72 7 0 20 May 2023
Mode Connectivity in Auction Design Christoph Hertrich Yixin Tao László A. Végh 69 1 0 18 May 2023
Efficient Asynchronize Stochastic Gradient Algorithm with Structured Data Zhao Song Mingquan Ye 67 4 0 13 May 2023
Function Approximation with Randomly Initialized Neural Networks for Approximate Model Reference Adaptive Control Tyler Lekang Andrew G. Lamperski 50 0 0 28 Mar 2023
Phase Diagram of Initial Condensation for Two-layer Neural Networks Zheng Chen Yuqing Li Yaoyu Zhang Zhaoguang Zhou Z. Xu MLT AI4CE 104 11 0 12 Mar 2023
Linear CNNs Discover the Statistical Structure of the Dataset Using Only the Most Dominant Frequencies Hannah Pinson Joeri Lenaerts V. Ginis 53 3 0 03 Mar 2023
Implicit Stochastic Gradient Descent for Training Physics-informed Neural Networks Ye Li Songcan Chen Shengyi Huang PINN 51 3 0 03 Mar 2023
On the existence of minimizers in shallow residual ReLU neural network optimization landscapes Steffen Dereich Arnulf Jentzen Sebastian Kassing 65 7 0 28 Feb 2023
Over-Parameterization Exponentially Slows Down Gradient Descent for Learning a Single Neuron Weihang Xu S. Du 105 16 0 20 Feb 2023
Global Convergence Rate of Deep Equilibrium Models with General Activations Lan V. Truong 127 2 0 11 Feb 2023
Rethinking Gauss-Newton for learning over-parameterized models Michael Arbel Romain Menegaux Pierre Wolinski AI4CE 82 6 0 06 Feb 2023