Non-Vacuous Generalization Bounds at the ImageNet Scale: A PAC-Bayesian Compression Approach

16 April 2018

Papers citing "Non-Vacuous Generalization Bounds at the ImageNet Scale: A PAC-Bayesian Compression Approach"

50 / 155 papers shown

Title
Compute-Optimal LLMs Provably Generalize Better With Scale Marc Finzi Sanyam Kapoor Diego Granziol Anming Gu Christopher De Sa J. Zico Kolter Andrew Gordon Wilson 30 0 0 21 Apr 2025
How good is PAC-Bayes at explaining generalisation? Antoine Picard-Weibel Eugenio Clerico Roman Moscoviz Benjamin Guedj 64 0 0 11 Mar 2025
Non-vacuous Generalization Bounds for Deep Neural Networks without any modification to the trained models Khoat Than Dat Phan BDL AAML VLM 60 0 0 10 Mar 2025
Deep Learning is Not So Mysterious or Different Andrew Gordon Wilson 41 2 0 03 Mar 2025
Unlocking the Potential of Text-to-Image Diffusion with PAC-Bayesian Theory Eric Hanchen Jiang Yasi Zhang Zhi Zhang Yixin Wan Andrew Lizarraga Shufan Li Ying Nian Wu DiffM 77 2 0 25 Nov 2024
Learning via Surrogate PAC-Bayes Antoine Picard-Weibel Roman Moscoviz Benjamin Guedj 25 0 0 14 Oct 2024
Efficient Source-Free Time-Series Adaptation via Parameter Subspace Disentanglement Gaurav Patel Christopher Sandino Behrooz Mahasseni Ellen L. Zippi Erdrin Azemi Ali Moin Juri Minxha TTA AI4TS 50 3 0 03 Oct 2024
Tightening the Evaluation of PAC Bounds Using Formal Verification Results Thomas Walker A. Lomuscio 24 0 0 29 Jul 2024
Unlocking Tokens as Data Points for Generalization Bounds on Larger Language Models Sanae Lotfi Yilun Kuang Brandon Amos Micah Goldblum Marc Finzi Andrew Gordon Wilson 31 8 0 25 Jul 2024
Exploring The Neural Burden In Pruned Models: An Insight Inspired By Neuroscience Zeyu Wang Weichen Dai Xiangyu Zhou Ji Qi Yi Zhou 48 0 0 23 Jul 2024
A Generalization Bound for Nearly-Linear Networks Eugene Golikov 31 0 0 09 Jul 2024
Information-Theoretic Generalization Bounds for Deep Neural Networks Haiyun He Christina Lee Yu 35 4 0 04 Apr 2024
Non-Vacuous Generalization Bounds for Large Language Models Sanae Lotfi Marc Finzi Yilun Kuang Tim G. J. Rudner Micah Goldblum Andrew Gordon Wilson 28 20 0 28 Dec 2023
A note on regularised NTK dynamics with an application to PAC-Bayesian training Eugenio Clerico Benjamin Guedj 33 0 0 20 Dec 2023
Perspectives on the State and Future of Deep Learning - 2023 Micah Goldblum A. Anandkumar Richard Baraniuk Tom Goldstein Kyunghyun Cho Zachary Chase Lipton Melanie Mitchell Preetum Nakkiran Max Welling Andrew Gordon Wilson 61 4 0 07 Dec 2023
Interpretability Illusions in the Generalization of Simplified Models Dan Friedman Andrew Kyle Lampinen Lucas Dixon Danqi Chen Asma Ghandeharioun 17 14 0 06 Dec 2023
Information-Theoretic Generalization Bounds for Transductive Learning and its Applications Huayi Tang Yong Liu 62 1 0 08 Nov 2023
Comparing Comparators in Generalization Bounds Fredrik Hellström Benjamin Guedj 28 4 0 16 Oct 2023
Understanding prompt engineering may not require rethinking generalization Victor Akinwande Yiding Jiang Dylan Sam J. Zico Kolter VLM VPVLM 123 7 0 06 Oct 2023
The fine print on tempered posteriors Konstantinos Pitas Julyan Arbel 30 1 0 11 Sep 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
Sparsity-aware generalization theory for deep neural networks Ramchandran Muthukumar Jeremias Sulam MLT 24 4 0 01 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 28 9 0 21 Jun 2023
MMD-FUSE: Learning and Combining Kernels for Two-Sample Testing Without Data Splitting Felix Biggs Antonin Schrab A. Gretton 17 19 0 14 Jun 2023
Lessons from Generalization Error Analysis of Federated Learning: You May Communicate Less Often! Milad Sefidgaran Romain Chor A. Zaidi Yijun Wan FedML 32 6 0 09 Jun 2023
Understanding Augmentation-based Self-Supervised Representation Learning via RKHS Approximation and Regression Runtian Zhai Bing Liu Andrej Risteski Zico Kolter Pradeep Ravikumar SSL 28 9 0 01 Jun 2023
(Almost) Provable Error Bounds Under Distribution Shift via Disagreement Discrepancy Elan Rosenfeld Saurabh Garg UQCV 34 4 0 01 Jun 2023
On the Role of Noise in the Sample Complexity of Learning Recurrent Neural Networks: Exponential Gaps for Long Sequences A. F. Pour H. Ashtiani 19 0 0 28 May 2023
Understanding the Generalization Ability of Deep Learning Algorithms: A Kernelized Renyi's Entropy Perspective Yuxin Dong Tieliang Gong H. Chen Chen Li 23 4 0 02 May 2023
The No Free Lunch Theorem, Kolmogorov Complexity, and the Role of Inductive Biases in Machine Learning Micah Goldblum Marc Finzi K. Rowan A. Wilson UQCV FedML 24 37 0 11 Apr 2023
Generalization Error Bounds for Noisy, Iterative Algorithms via Maximal Leakage Ibrahim Issa A. Esposito Michael C. Gastpar 29 2 0 28 Feb 2023
Tighter PAC-Bayes Bounds Through Coin-Betting Kyoungseok Jang Kwang-Sung Jun Ilja Kuzborskij Francesco Orabona 26 15 0 12 Feb 2023
Gradient Descent in Neural Networks as Sequential Learning in RKBS A. Shilton Sunil R. Gupta Santu Rana Svetha Venkatesh MLT 11 1 0 01 Feb 2023
Norm-based Generalization Bounds for Compositionally Sparse Neural Networks Tomer Galanti Mengjia Xu Liane Galanti T. Poggio 30 9 0 28 Jan 2023
Lifelong Reinforcement Learning with Modulating Masks Eseoghene Ben-Iwhiwhu Saptarshi Nath Praveen K. Pilly Soheil Kolouri Andrea Soltoggio CLL OffRL 32 20 0 21 Dec 2022
PAC-Bayes Compression Bounds So Tight That They Can Explain Generalization Sanae Lotfi Marc Finzi Sanyam Kapoor Andres Potapczynski Micah Goldblum A. Wilson BDL MLT AI4CE 29 51 0 24 Nov 2022
Instance-Dependent Generalization Bounds via Optimal Transport Songyan Hou Parnian Kassraie Anastasis Kratsios Andreas Krause Jonas Rothfuss 22 6 0 02 Nov 2022
Tighter PAC-Bayes Generalisation Bounds by Leveraging Example Difficulty Felix Biggs Benjamin Guedj 24 7 0 20 Oct 2022
Toward Sustainable Continual Learning: Detection and Knowledge Repurposing of Similar Tasks Sijia Wang Yoojin Choi Junya Chen Mostafa El-Khamy Ricardo Henao CLL 22 0 0 11 Oct 2022
Scale-invariant Bayesian Neural Networks with Connectivity Tangent Kernel Sungyub Kim Si-hun Park Kyungsu Kim Eunho Yang BDL 29 4 0 30 Sep 2022
Generalisation under gradient descent via deterministic PAC-Bayes Eugenio Clerico Tyler Farghly George Deligiannidis Benjamin Guedj Arnaud Doucet 31 4 0 06 Sep 2022
Efficient Concentration with Gaussian Approximation Morgane Austern Lester W. Mackey 13 2 0 21 Aug 2022
On the generalization of learning algorithms that do not converge N. Chandramoorthy Andreas Loukas Khashayar Gatmiry Stefanie Jegelka MLT 19 11 0 16 Aug 2022
On Rademacher Complexity-based Generalization Bounds for Deep Learning Lan V. Truong MLT 39 13 0 08 Aug 2022
Bounding generalization error with input compression: An empirical study with infinite-width networks A. Galloway A. Golubeva Mahmoud Salem Mihai Nica Yani Andrew Ioannou Graham W. Taylor MLT AI4CE 24 4 0 19 Jul 2022
PAC-Bayesian Domain Adaptation Bounds for Multiclass Learners Anthony Sicilia Katherine Atwell Malihe Alikhani Seong Jae Hwang BDL 51 9 0 12 Jul 2022
Benefits of Additive Noise in Composing Classes with Bounded Capacity A. F. Pour H. Ashtiani 33 3 0 14 Jun 2022
On Margins and Generalisation for Voting Classifiers Felix Biggs Valentina Zantedeschi Benjamin Guedj 25 8 0 09 Jun 2022
Trajectory-dependent Generalization Bounds for Deep Neural Networks via Fractional Brownian Motion Chengli Tan Jiang Zhang Junmin Liu 35 1 0 09 Jun 2022
Robust Fine-Tuning of Deep Neural Networks with Hessian-based Generalization Guarantees Haotian Ju Dongyue Li Hongyang R. Zhang 40 28 0 06 Jun 2022