v1v2v3v4 (latest)

Generalisation under gradient descent via deterministic PAC-Bayes

6 September 2022

George Deligiannidis

Papers citing "Generalisation under gradient descent via deterministic PAC-Bayes"

50 / 57 papers shown

Title
Non-vacuous Generalization Bounds for Deep Neural Networks without any modification to the trained models Khoat Than Dat Phan BDL AAML VLM 91 0 0 10 Mar 2025
Understanding the Generalization Error of Markov algorithms through Poissonization Benjamin Dupuis Maxime Haddouche George Deligiannidis Umut Simsekli 86 0 0 11 Feb 2025
A note on regularised NTK dynamics with an application to PAC-Bayesian training Eugenio Clerico Benjamin Guedj 84 0 0 20 Dec 2023
Algorithmic Stability of Heavy-Tailed SGD with General Loss Functions Anant Raj Lingjiong Zhu Mert Gurbuzbalaban Umut Simsekli 55 16 0 27 Jan 2023
Chained Generalisation Bounds Eugenio Clerico Amitis Shidani George Deligiannidis Arnaud Doucet AI4CE FedML 71 13 0 02 Mar 2022
Generalization Bounds via Convex Analysis Gábor Lugosi Gergely Neu 55 29 0 10 Feb 2022
Non-Vacuous Generalisation Bounds for Shallow Neural Networks Felix Biggs Benjamin Guedj BDL 82 26 0 03 Feb 2022
Time-independent Generalization Bounds for SGLD in Non-convex Settings Tyler Farghly Patrick Rebeschini 73 24 0 25 Nov 2021
Conditionally Gaussian PAC-Bayes Eugenio Clerico George Deligiannidis Arnaud Doucet 88 10 0 22 Oct 2021
User-friendly introduction to PAC-Bayes bounds Pierre Alquier FedML 154 204 0 21 Oct 2021
Learning PAC-Bayes Priors for Probabilistic Neural Networks Maria Perez-Ortiz Omar Rivasplata Benjamin Guedj M. Gleeson Jingyu Zhang John Shawe-Taylor M. Bober J. Kittler UQCV 96 31 0 21 Sep 2021
On Margins and Derandomisation in PAC-Bayes Felix Biggs Benjamin Guedj 64 20 0 08 Jul 2021
Learning Stochastic Majority Votes by Minimizing a PAC-Bayes Generalization Bound Valentina Zantedeschi Paul Viallard Emilie Morvant Rémi Emonet Amaury Habrard Pascal Germain Benjamin Guedj FedML BDL 57 17 0 23 Jun 2021
Label Noise SGD Provably Prefers Flat Global Minimizers Alexandru Damian Tengyu Ma Jason D. Lee NoLa 99 119 0 11 Jun 2021
Tensor Programs IIb: Architectural Universality of Neural Tangent Kernel Training Dynamics Greg Yang Etai Littwin 70 66 0 08 May 2021
Information-Theoretic Generalization Bounds for Stochastic Gradient Descent Gergely Neu Gintare Karolina Dziugaite Mahdi Haghifam Daniel M. Roy 68 90 0 01 Feb 2021
A Deeper Look at the Hessian Eigenspectrum of Deep Neural Networks and its Applications to Regularization Adepu Ravi Sankar Yash Khasbage Rahul Vigneswaran V. Balasubramanian 74 44 0 07 Dec 2020
Score-Based Generative Modeling through Stochastic Differential Equations Yang Song Jascha Narain Sohl-Dickstein Diederik P. Kingma Abhishek Kumar Stefano Ermon Ben Poole DiffM SyDa 341 6,480 0 26 Nov 2020
Tighter risk certificates for neural networks Maria Perez-Ortiz Omar Rivasplata John Shawe-Taylor Csaba Szepesvári UQCV 78 106 0 25 Jul 2020
PAC-Bayes Analysis Beyond the Usual Bounds Omar Rivasplata Ilja Kuzborskij Csaba Szepesvári John Shawe-Taylor 81 80 0 23 Jun 2020
Differentiable PAC-Bayes Objectives with Partially Aggregated Neural Networks Felix Biggs Benjamin Guedj FedML UQCV BDL 28 34 0 22 Jun 2020
De-randomized PAC-Bayes Margin Bounds: Applications to Non-convex and Non-smooth Predictors A. Banerjee Tiancong Chen Yingxue Zhou BDL 46 8 0 23 Feb 2020
Information-Theoretic Generalization Bounds for SGLD via Data-Dependent Estimates Jeffrey Negrea Mahdi Haghifam Gintare Karolina Dziugaite Ashish Khisti Daniel M. Roy FedML 157 153 0 06 Nov 2019
Sharper bounds for uniformly stable algorithms Olivier Bousquet Yegor Klochkov Nikita Zhivotovskiy 59 122 0 17 Oct 2019
The generalization error of random features regression: Precise asymptotics and double descent curve Song Mei Andrea Montanari 86 635 0 14 Aug 2019
PAC-Bayesian Transportation Bound Kohei Miyaguchi 40 5 0 31 May 2019
Deterministic PAC-Bayesian generalization bounds for deep networks via generalizing noise-resilience Vaishnavh Nagarajan J. Zico Kolter 87 100 0 30 May 2019
Dichotomize and Generalize: PAC-Bayesian Binary Activated Deep Neural Networks Gaël Letarte Pascal Germain Benjamin Guedj Franccois Laviolette MQ AI4CE UQCV 70 54 0 24 May 2019
Linearized two-layers neural networks in high dimension Behrooz Ghorbani Song Mei Theodor Misiakiewicz Andrea Montanari MLT 57 243 0 27 Apr 2019
Implicit regularization for deep neural networks driven by an Ornstein-Uhlenbeck like process Guy Blanc Neha Gupta Gregory Valiant Paul Valiant 138 146 0 19 Apr 2019
Conformal Symplectic and Relativistic Optimization G. Francca Jeremias Sulam Daniel P. Robinson René Vidal 44 69 0 11 Mar 2019
High probability generalization bounds for uniformly stable algorithms with nearly optimal rate Vitaly Feldman J. Vondrák 70 155 0 27 Feb 2019
Wide Neural Networks of Any Depth Evolve as Linear Models Under Gradient Descent Jaehoon Lee Lechao Xiao S. Schoenholz Yasaman Bahri Roman Novak Jascha Narain Sohl-Dickstein Jeffrey Pennington 211 1,104 0 18 Feb 2019
Asymmetric Valleys: Beyond Sharp and Flat Local Minima Haowei He Gao Huang Yang Yuan ODL MLT 69 150 0 02 Feb 2019
An Investigation into Neural Net Optimization via Hessian Eigenvalue Density Behrooz Ghorbani Shankar Krishnan Ying Xiao ODL 67 324 0 29 Jan 2019
A Primer on PAC-Bayesian Learning Benjamin Guedj 156 222 0 16 Jan 2019
Generalization Bounds for Uniformly Stable Algorithms Vitaly Feldman J. Vondrák 49 89 0 24 Dec 2018
Global Non-convex Optimization with Discretized Diffusions Murat A. Erdogdu Lester W. Mackey Ohad Shamir 69 105 0 29 Oct 2018
Neural Tangent Kernel: Convergence and Generalization in Neural Networks Arthur Jacot Franck Gabriel Clément Hongler 267 3,203 0 20 Jun 2018
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 417 5,111 0 19 Jun 2018
Non-Vacuous Generalization Bounds at the ImageNet Scale: A PAC-Bayesian Compression Approach Wenda Zhou Victor Veitch Morgane Austern Ryan P. Adams Peter Orbanz 75 213 0 16 Apr 2018
Averaging Weights Leads to Wider Optima and Better Generalization Pavel Izmailov Dmitrii Podoprikhin T. Garipov Dmitry Vetrov A. Wilson FedML MoMe 133 1,662 0 14 Mar 2018
Generalization Error Bounds for Noisy, Iterative Algorithms Ankit Pensia Varun Jog Po-Ling Loh 74 113 0 12 Jan 2018
A PAC-Bayesian Approach to Spectrally-Normalized Margin Bounds for Neural Networks Behnam Neyshabur Srinadh Bhojanapalli Nathan Srebro 83 609 0 29 Jul 2017
Generalization Bounds of SGLD for Non-convex Learning: Two Theoretical Viewpoints Wenlong Mou Liwei Wang Xiyu Zhai Kai Zheng MLT 52 158 0 19 Jul 2017
Spectrally-normalized margin bounds for neural networks Peter L. Bartlett Dylan J. Foster Matus Telgarsky ODL 205 1,220 0 26 Jun 2017
Empirical Analysis of the Hessian of Over-Parametrized Neural Networks Levent Sagun Utku Evci V. U. Güney Yann N. Dauphin Léon Bottou 54 418 0 14 Jun 2017
Information-theoretic analysis of generalization capability of learning algorithms Aolin Xu Maxim Raginsky 169 446 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 106 815 0 31 Mar 2017
Non-convex learning via Stochastic Gradient Langevin Dynamics: a nonasymptotic analysis Maxim Raginsky Alexander Rakhlin Matus Telgarsky 73 521 0 13 Feb 2017