Computing Nonvacuous Generalization Bounds for Deep (Stochastic) Neural Networks with Many More Parameters than Training Data

31 March 2017

Papers citing "Computing Nonvacuous Generalization Bounds for Deep (Stochastic) Neural Networks with Many More Parameters than Training Data"

50 / 168 papers shown

Title
Generalization Guarantees for Multi-View Representation Learning and Application to Regularization via Gaussian Product Mixture Prior Milad Sefidgaran Abdellatif Zaidi Piotr Krasnowski 44 0 0 25 Apr 2025
SplatPose: Geometry-Aware 6-DoF Pose Estimation from Single RGB Image via 3D Gaussian Splatting Linqi Yang Xiongwei Zhao Qihao Sun Ke Wang Ao Chen Peng Kang 3DGS 76 2 0 07 Mar 2025
Generalization Guarantees for Representation Learning via Data-Dependent Gaussian Mixture Priors Milad Sefidgaran A. Zaidi Piotr Krasnowski 85 1 0 21 Feb 2025
Stability-based Generalization Bounds for Variational Inference Yadi Wei R. Khardon BDL 44 0 0 17 Feb 2025
Universal Sharpness Dynamics in Neural Network Training: Fixed Point Analysis, Edge of Stability, and Route to Chaos Dayal Singh Kalra Tianyu He M. Barkeshli 47 4 0 17 Feb 2025
Model Diffusion for Certifiable Few-shot Transfer Learning Fady Rezk Royson Lee H. Gouk Timothy M. Hospedales Minyoung Kim 48 0 0 10 Feb 2025
Evolutionary Optimization of Model Merging Recipes Takuya Akiba Makoto Shing Yujin Tang Qi Sun David Ha MoMe 105 99 0 28 Jan 2025
Seeking Consistent Flat Minima for Better Domain Generalization via Refining Loss Landscapes Aodi Li Liansheng Zhuang Xiao Long Minghong Yao Shafei Wang 180 0 0 18 Dec 2024
Understanding Generalization of Federated Learning: the Trade-off between Model Stability and Optimization Dun Zeng Zheshun Wu Shiyu Liu Yu Pan Xiaoying Tang Zenglin Xu MLT FedML 87 1 0 25 Nov 2024
Understanding Generalization in Quantum Machine Learning with Margins Tak Hur Daniel K. Park AI4CE 26 1 0 11 Nov 2024
Multi-View Majority Vote Learning Algorithms: Direct Minimization of PAC-Bayesian Bounds Mehdi Hennequin Abdelkrim Zitouni K. Benabdeslem H. Elghazel Yacine Gaci 26 0 0 09 Nov 2024
Theoretical characterisation of the Gauss-Newton conditioning in Neural Networks Jim Zhao Sidak Pal Singh Aurélien Lucchi AI4CE 39 0 0 04 Nov 2024
MomentumSMoE: Integrating Momentum into Sparse Mixture of Experts R. Teo Tan M. Nguyen MoE 31 3 0 18 Oct 2024
OledFL: Unleashing the Potential of Decentralized Federated Learning via Opposite Lookahead Enhancement Qinglun Li Miao Zhang Mengzhu Wang Quanjun Yin Li Shen OODD FedML 19 0 0 09 Oct 2024
QT-DoG: Quantization-aware Training for Domain Generalization Saqib Javed Hieu Le Mathieu Salzmann OOD MQ 28 1 0 08 Oct 2024
Can Optimization Trajectories Explain Multi-Task Transfer? David Mueller Mark Dredze Nicholas Andrews 53 1 0 26 Aug 2024
Just How Flexible are Neural Networks in Practice? Ravid Shwartz-Ziv Micah Goldblum Arpit Bansal C. B. Bruss Yann LeCun Andrew Gordon Wilson 37 4 0 17 Jun 2024
What Does Softmax Probability Tell Us about Classifiers Ranking Across Diverse Test Conditions? Weijie Tu Weijian Deng Liang Zheng Tom Gedeon 37 0 0 14 Jun 2024
Agnostic Sharpness-Aware Minimization Van-Anh Nguyen Quyen Tran Tuan Truong Thanh-Toan Do Dinh Q. Phung Trung Le 38 0 0 11 Jun 2024
A Margin-based Multiclass Generalization Bound via Geometric Complexity Michael Munn Benoit Dherin Javier Gonzalvo UQCV 40 2 0 28 May 2024
Recursive PAC-Bayes: A Frequentist Approach to Sequential Prior Updates with No Information Loss Yi-Shan Wu Yijie Zhang Badr-Eddine Chérief-Abdellatif Yevgeny Seldin 26 1 0 23 May 2024
Why is SAM Robust to Label Noise? Christina Baek Zico Kolter Aditi Raghunathan NoLa AAML 41 9 0 06 May 2024
Uniform Generalization Bounds on Data-Dependent Hypothesis Sets via PAC-Bayesian Theory on Random Sets Benjamin Dupuis Paul Viallard George Deligiannidis Umut Simsekli 40 2 0 26 Apr 2024
Flatness Improves Backbone Generalisation in Few-shot Classification Rui Li Martin Trapp Marcus Klasson Arno Solin 43 0 0 11 Apr 2024
Information-Theoretic Generalization Bounds for Deep Neural Networks Haiyun He Christina Lee Yu 35 4 0 04 Apr 2024
Leveraging PAC-Bayes Theory and Gibbs Distributions for Generalization Bounds with Complexity Measures Paul Viallard Rémi Emonet Amaury Habrard Emilie Morvant Valentina Zantedeschi 33 3 0 19 Feb 2024
A PAC-Bayesian Link Between Generalisation and Flat Minima Maxime Haddouche Paul Viallard Umut Simsekli Benjamin Guedj 35 3 0 13 Feb 2024
Critical Influence of Overparameterization on Sharpness-aware Minimization Sungbin Shin Dongyeop Lee Maksym Andriushchenko Namhoon Lee AAML 44 1 0 29 Nov 2023
Information-Theoretic Generalization Bounds for Transductive Learning and its Applications Huayi Tang Yong Liu 57 1 0 08 Nov 2023
Investigating the Ability of PINNs To Solve Burgers' PDE Near Finite-Time BlowUp Dibyakanti Kumar Anirbit Mukherjee 31 2 0 08 Oct 2023
Lookbehind-SAM: k steps back, 1 step forward Gonçalo Mordido Pranshu Malviya A. Baratin Sarath Chandar AAML 40 1 0 31 Jul 2023
Understanding Deep Neural Networks via Linear Separability of Hidden Layers Chao Zhang Xinyuan Chen Wensheng Li Lixue Liu Wei Wu Dacheng Tao 18 3 0 26 Jul 2023
Sharpness Minimization Algorithms Do Not Only Minimize Sharpness To Achieve Better Generalization Kaiyue Wen Zhiyuan Li Tengyu Ma FAtt 36 26 0 20 Jul 2023
Source-Aware Embedding Training on Heterogeneous Information Networks Tsai Hor Chan Chi Ho Wong Jiajun Shen Guosheng Yin 27 4 0 10 Jul 2023
More PAC-Bayes bounds: From bounded losses, to losses with general tail behaviors, to anytime validity Borja Rodríguez Gálvez Ragnar Thobaben Mikael Skoglund 26 9 0 21 Jun 2023
How to escape sharp minima with random perturbations Kwangjun Ahn Ali Jadbabaie S. Sra ODL 26 6 0 25 May 2023
An Adaptive Policy to Employ Sharpness-Aware Minimization Weisen Jiang Hansi Yang Yu Zhang James T. Kwok AAML 81 31 0 28 Apr 2023
Fundamental Tradeoffs in Learning with Prior Information Anirudha Majumdar 27 0 0 26 Apr 2023
Generalization Matters: Loss Minima Flattening via Parameter Hybridization for Efficient Online Knowledge Distillation Tianli Zhang Mengqi Xue Jiangtao Zhang Haofei Zhang Yu Wang Lechao Cheng Jie Song Mingli Song 28 5 0 26 Mar 2023
Randomized Adversarial Training via Taylor Expansion Gao Jin Xinping Yi Dengyu Wu Ronghui Mu Xiaowei Huang AAML 36 34 0 19 Mar 2023
DiTTO: A Feature Representation Imitation Approach for Improving Cross-Lingual Transfer Shanu Kumar Abbaraju Soujanya Sandipan Dandapat Sunayana Sitaram Monojit Choudhury VLM 25 1 0 04 Mar 2023
DART: Diversify-Aggregate-Repeat Training Improves Generalization of Neural Networks Samyak Jain Sravanti Addepalli P. Sahu Priyam Dey R. Venkatesh Babu MoMe OOD 35 20 0 28 Feb 2023
mSAM: Micro-Batch-Averaged Sharpness-Aware Minimization Kayhan Behdin Qingquan Song Aman Gupta S. Keerthi Ayan Acharya Borja Ocejo Gregory Dexter Rajiv Khanna D. Durfee Rahul Mazumder AAML 13 7 0 19 Feb 2023
Global Convergence Rate of Deep Equilibrium Models with General Activations Lan V. Truong 37 2 0 11 Feb 2023
Generalization in Graph Neural Networks: Improved PAC-Bayesian Bounds on Graph Diffusion Haotian Ju Dongyue Li Aneesh Sharma Hongyang R. Zhang 23 40 0 09 Feb 2023
PAC-Bayesian Soft Actor-Critic Learning Bahareh Tasdighi Abdullah Akgul Manuel Haussmann Kenny Kazimirzak Brink M. Kandemir 26 3 0 30 Jan 2023
Exploring the Effect of Multi-step Ascent in Sharpness-Aware Minimization Hoki Kim Jinseong Park Yujin Choi Woojin Lee Jaewook Lee 15 9 0 27 Jan 2023
An SDE for Modeling SAM: Theory and Insights Enea Monzio Compagnoni Luca Biggio Antonio Orvieto F. Proske Hans Kersting Aurélien Lucchi 21 13 0 19 Jan 2023
Stability Analysis of Sharpness-Aware Minimization Hoki Kim Jinseong Park Yujin Choi Jaewook Lee 28 12 0 16 Jan 2023
WLD-Reg: A Data-dependent Within-layer Diversity Regularizer Firas Laakom Jenni Raitoharju Alexandros Iosifidis M. Gabbouj AI4CE 23 7 0 03 Jan 2023