Temperature is All You Need for Generalization in Langevin Dynamics and other Markov Processes

25 May 2025

Papers citing "Temperature is All You Need for Generalization in Langevin Dynamics and other Markov Processes"

31 / 31 papers shown

Title
Uniform Generalization Bounds on Data-Dependent Hypothesis Sets via PAC-Bayesian Theory on Random Sets Benjamin Dupuis Paul Viallard George Deligiannidis Umut Simsekli 79 4 0 26 Apr 2024
How Uniform Random Weights Induce Non-uniform Bias: Typical Interpolating Neural Networks Generalize with Narrow Teachers G. Buzaglo I. Harel Mor Shpigel Nacson Alon Brutzkus Nathan Srebro Daniel Soudry 75 6 0 09 Feb 2024
Time-Independent Information-Theoretic Generalization Bounds for SGLD Futoshi Futami Masahiro Fujisawa 62 7 0 02 Nov 2023
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 43 60 0 24 Nov 2022
Stability and Generalization Analysis of Gradient Methods for Shallow Neural Networks Yunwen Lei Rong Jin Yiming Ying MLT 79 19 0 19 Sep 2022
Time-independent Generalization Bounds for SGLD in Non-convex Settings Tyler Farghly Patrick Rebeschini 51 24 0 25 Nov 2021
User-friendly introduction to PAC-Bayes bounds Pierre Alquier FedML 118 202 0 21 Oct 2021
Stochastic Training is Not Necessary for Generalization Jonas Geiping Micah Goldblum Phillip E. Pope Michael Moeller Tom Goldstein 121 75 0 29 Sep 2021
Random Neural Networks in the Infinite Width Limit as Gaussian Processes Boris Hanin BDL 48 47 0 04 Jul 2021
Learning with Gradient Descent and Weakly Convex Losses Dominic Richards Michael G. Rabbat MLT 48 14 0 13 Jan 2021
On the role of data in PAC-Bayes bounds Gintare Karolina Dziugaite Kyle Hsu W. Gharbieh Gabriel Arpino Daniel M. Roy 49 78 0 19 Jun 2020
On Generalization Error Bounds of Noisy Gradient Methods for Non-Convex Learning Jian Li Xuanyuan Luo Mingda Qiao 41 88 0 02 Feb 2019
Neural Tangent Kernel: Convergence and Generalization in Neural Networks Arthur Jacot Franck Gabriel Clément Hongler 188 3,160 0 20 Jun 2018
Gaussian Process Behaviour in Wide Deep Neural Networks A. G. Matthews Mark Rowland Jiri Hron Richard Turner Zoubin Ghahramani BDL 122 553 0 30 Apr 2018
A Mean Field View of the Landscape of Two-Layers Neural Networks Song Mei Andrea Montanari Phan-Minh Nguyen MLT 76 855 0 18 Apr 2018
Stronger generalization bounds for deep nets via a compression approach Sanjeev Arora Rong Ge Behnam Neyshabur Yi Zhang MLT AI4CE 74 637 0 14 Feb 2018
Size-Independent Sample Complexity of Neural Networks Noah Golowich Alexander Rakhlin Ohad Shamir 97 547 0 18 Dec 2017
Deep Neural Networks as Gaussian Processes Jaehoon Lee Yasaman Bahri Roman Novak S. Schoenholz Jeffrey Pennington Jascha Narain Sohl-Dickstein UQCV BDL 109 1,086 0 01 Nov 2017
Generalization Bounds of SGLD for Non-convex Learning: Two Theoretical Viewpoints Wenlong Mou Liwei Wang Xiyu Zhai Kai Zheng MLT 47 156 0 19 Jul 2017
Spectrally-normalized margin bounds for neural networks Peter L. Bartlett Dylan J. Foster Matus Telgarsky ODL 135 1,208 0 26 Jun 2017
Implicit Regularization in Matrix Factorization Suriya Gunasekar Blake E. Woodworth Srinadh Bhojanapalli Behnam Neyshabur Nathan Srebro 65 490 0 25 May 2017
Information-theoretic analysis of generalization capability of learning algorithms Aolin Xu Maxim Raginsky 111 442 0 22 May 2017
Computing Nonvacuous Generalization Bounds for Deep (Stochastic) Neural Networks with Many More Parameters than Training Data Gintare Karolina Dziugaite Daniel M. Roy 85 808 0 31 Mar 2017
How to Escape Saddle Points Efficiently Chi Jin Rong Ge Praneeth Netrapalli Sham Kakade Michael I. Jordan ODL 169 834 0 02 Mar 2017
Non-convex learning via Stochastic Gradient Langevin Dynamics: a nonasymptotic analysis Maxim Raginsky Alexander Rakhlin Matus Telgarsky 62 518 0 13 Feb 2017
Understanding deep learning requires rethinking generalization Chiyuan Zhang Samy Bengio Moritz Hardt Benjamin Recht Oriol Vinyals HAI 269 4,620 0 10 Nov 2016
How much does your data exploration overfit? Controlling bias via information usage D. Russo James Zou 34 189 0 16 Nov 2015
Train faster, generalize better: Stability of stochastic gradient descent Moritz Hardt Benjamin Recht Y. Singer 96 1,234 0 03 Sep 2015
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification Kaiming He Xinming Zhang Shaoqing Ren Jian Sun VLM 200 18,534 0 06 Feb 2015
Rényi Divergence and Kullback-Leibler Divergence T. Erven P. Harremoes 60 1,326 0 12 Jun 2012
Pac-Bayesian Supervised Classification: The Thermodynamics of Statistical Learning O. Catoni 232 458 0 03 Dec 2007