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Stochastic Gradient Descent as Approximate Bayesian Inference

13 April 2017

Matthew D. Hoffman

Papers citing "Stochastic Gradient Descent as Approximate Bayesian Inference"

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Title
Distributional Training Data Attribution Bruno Mlodozeniec Isaac Reid Sam Power David M. Krueger Murat Erdogdu Richard E. Turner Roger B. Grosse TDI OOD 40 0 0 15 Jun 2025
SGD as Free Energy Minimization: A Thermodynamic View on Neural Network Training Ildus Sadrtdinov Ivan Klimov E. Lobacheva Dmitry Vetrov 28 0 0 29 May 2025
PADAM: Parallel averaged Adam reduces the error for stochastic optimization in scientific machine learning Arnulf Jentzen Julian Kranz Adrian Riekert ODL 43 0 0 28 May 2025
A Unified Gradient-based Framework for Task-agnostic Continual Learning-Unlearning Zhehao Huang Xinwen Cheng Jing Zhang Jinghao Zheng Haoran Wang Zhengbao He Tao Li Xiaolin Huang CLL 85 1 0 21 May 2025
Seeking Flat Minima over Diverse Surrogates for Improved Adversarial Transferability: A Theoretical Framework and Algorithmic Instantiation Meixi Zheng Kehan Wu Yanbo Fan Rui Huang Baoyuan Wu AAML 74 0 0 23 Apr 2025
Bayesian Pseudo Posterior Mechanism for Differentially Private Machine Learning Robert Chew Matthew R. Williams Elan A. Segarra Alexander J. Preiss Amanda Konet T. Savitsky 81 0 0 27 Mar 2025
On Local Posterior Structure in Deep Ensembles Mikkel Jordahn Jonas Vestergaard Jensen Mikkel N. Schmidt Michael Riis Andersen UQCV BDL OOD 149 0 0 17 Mar 2025
Entropy-regularized Gradient Estimators for Approximate Bayesian Inference Jasmeet Kaur BDL UQCV 124 0 0 15 Mar 2025
NoT: Federated Unlearning via Weight Negation Yasser H. Khalil Leo Maxime Brunswic Soufiane Lamghari Xu Li Mahdi Beitollahi Xi Chen MU 127 2 0 07 Mar 2025
Generative Uncertainty in Diffusion Models Metod Jazbec Eliot Wong-Toi Guoxuan Xia Dan Zhang Eric T. Nalisnick Stephan Mandt DiffM 127 1 0 28 Feb 2025
Reinforcement Teaching Alex Lewandowski Calarina Muslimani Dale Schuurmans Matthew E. Taylor Jun Luo 192 2 0 28 Jan 2025
Soft Condorcet Optimization for Ranking of General Agents Marc Lanctot Kate Larson Michael Kaisers Quentin Berthet I. Gemp Manfred Diaz Roberto-Rafael Maura-Rivero Yoram Bachrach Anna Koop Doina Precup 270 0 0 31 Oct 2024
Bayes without Underfitting: Fully Correlated Deep Learning Posteriors via Alternating Projections M. Miani Hrittik Roy Søren Hauberg UQCV BDL 112 0 0 22 Oct 2024
Influential Language Data Selection via Gradient Trajectory Pursuit Zhiwei Deng Tao Li Yang Li 62 1 0 22 Oct 2024
Understanding Adversarially Robust Generalization via Weight-Curvature Index Yuelin Xu Xiao Zhang AAML 61 0 0 10 Oct 2024
Robust Adaptation of Foundation Models with Black-Box Visual Prompting Changdae Oh Gyeongdeok Seo Geunyoung Jung Zhi-Qi Cheng Hosik Choi Jiyoung Jung Kyungwoo Song VLM 125 1 0 04 Jul 2024
On the Trade-off between Flatness and Optimization in Distributed Learning Ying Cao Zhaoxian Wu Kun Yuan Ali H. Sayed 103 1 0 28 Jun 2024
Effect of Random Learning Rate: Theoretical Analysis of SGD Dynamics in Non-Convex Optimization via Stationary Distribution Naoki Yoshida Shogo H. Nakakita Masaaki Imaizumi 62 1 0 23 Jun 2024
Do Parameters Reveal More than Loss for Membership Inference? Anshuman Suri Xiao Zhang David Evans MIACV MIALM AAML 92 1 0 17 Jun 2024
Score-based Generative Models with Adaptive Momentum Ziqing Wen Xiaoge Deng Ping Luo Tao Sun Dongsheng Li DiffM 57 0 0 22 May 2024
UPAM: Unified Prompt Attack in Text-to-Image Generation Models Against Both Textual Filters and Visual Checkers Duo Peng Qi Ke Jun Liu 83 4 0 18 May 2024
Constrained Exploration via Reflected Replica Exchange Stochastic Gradient Langevin Dynamics Haoyang Zheng Hengrong Du Qi Feng Wei Deng Guang Lin 65 5 0 13 May 2024
Variational Stochastic Gradient Descent for Deep Neural Networks Haotian Chen Anna Kuzina Babak Esmaeili Jakub M. Tomczak 106 0 0 09 Apr 2024
Upper Bound of Bayesian Generalization Error in Partial Concept Bottleneck Model (CBM): Partial CBM outperforms naive CBM Naoki Hayashi Yoshihide Sawada 70 1 0 14 Mar 2024
Scalable Bayesian inference for the generalized linear mixed model S. Berchuck Felipe A. Medeiros Sayan Mukherjee Andrea Agazzi 65 0 0 05 Mar 2024
Batch size invariant Adam Xi Wang Laurence Aitchison 87 2 0 29 Feb 2024
Pre-training Differentially Private Models with Limited Public Data Zhiqi Bu Xinwei Zhang Mingyi Hong Sheng Zha George Karypis 114 4 0 28 Feb 2024
Diffusion Models as Constrained Samplers for Optimization with Unknown Constraints Lingkai Kong Yuanqi Du Wenhao Mu Kirill Neklyudov Valentin De Bortol ... D. Wu Aaron Ferber Yi-An Ma Carla P. Gomes Chao Zhang 82 13 0 28 Feb 2024
Stochastic Gradient Flow Dynamics of Test Risk and its Exact Solution for Weak Features Rodrigo Veiga Anastasia Remizova Nicolas Macris 74 1 0 12 Feb 2024
On the Impact of Output Perturbation on Fairness in Binary Linear Classification Vitalii Emelianov Michael Perrot FaML 98 0 0 05 Feb 2024
Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI Theodore Papamarkou Maria Skoularidou Konstantina Palla Laurence Aitchison Julyan Arbel ... David Rügamer Yee Whye Teh Max Welling Andrew Gordon Wilson Ruqi Zhang UQCV BDL 133 35 0 01 Feb 2024
RADIN: Souping on a Budget Thibaut Menes Olivier Risser-Maroix MoMe 104 1 0 31 Jan 2024
Querying Easily Flip-flopped Samples for Deep Active Learning S. Cho G. Kim Junghyun Lee Jinwoo Shin Chang D. Yoo 96 6 0 18 Jan 2024
Stabilizing Sharpness-aware Minimization Through A Simple Renormalization Strategy Chengli Tan Jiangshe Zhang Junmin Liu Yicheng Wang Yunda Hao AAML 73 2 0 14 Jan 2024
DiffHybrid-UQ: Uncertainty Quantification for Differentiable Hybrid Neural Modeling Deepak Akhare Tengfei Luo Jian-Xun Wang 74 6 0 30 Dec 2023
Learning to Infer Unobserved Behaviors: Estimating User's Preference for a Site over Other Sites Atanu R. Sinha Tanay Anand Paridhi Maheshwari A. V. Lakshmy Vishal Jain 18 0 0 15 Dec 2023
Fusing Multiple Algorithms for Heterogeneous Online Learning D. Gadginmath Shivanshu Tripathi Fabio Pasqualetti FedML 40 1 0 09 Dec 2023
Weight fluctuations in (deep) linear neural networks and a derivation of the inverse-variance flatness relation Markus Gross A. Raulf Christoph Räth 110 0 0 23 Nov 2023
Trustworthy Large Models in Vision: A Survey Ziyan Guo Li Xu Jun Liu MU 126 0 0 16 Nov 2023
Signal Processing Meets SGD: From Momentum to Filter Zhipeng Yao Guisong Chang Jiaqi Zhang Qi Zhang Dazhou Li Yu Zhang ODL 105 0 0 06 Nov 2023
Seeking Flat Minima with Mean Teacher on Semi- and Weakly-Supervised Domain Generalization for Object Detection Ryosuke Furuta Yoichi Sato 104 0 0 30 Oct 2023
On the accuracy and efficiency of group-wise clipping in differentially private optimization Zhiqi Bu Ruixuan Liu Yu Wang Sheng Zha George Karypis VLM 66 4 0 30 Oct 2023
Out-of-distribution Object Detection through Bayesian Uncertainty Estimation Tianhao Zhang Shenglin Wang N. Bouaynaya R. Calinescu Lyudmila Mihaylova OODD 64 2 0 29 Oct 2023
Butterfly Effects of SGD Noise: Error Amplification in Behavior Cloning and Autoregression Adam Block Dylan J. Foster Akshay Krishnamurthy Max Simchowitz Cyril Zhang 75 7 0 17 Oct 2023
On permutation symmetries in Bayesian neural network posteriors: a variational perspective Simone Rossi Ankit Singh T. Hannagan 69 3 0 16 Oct 2023
Approximating Nash Equilibria in Normal-Form Games via Stochastic Optimization I. Gemp Luke Marris Georgios Piliouras 81 9 0 10 Oct 2023
Coupling public and private gradient provably helps optimization Ruixuan Liu Zhiqi Bu Yu Wang Sheng Zha George Karypis 73 2 0 02 Oct 2023
A Primer on Bayesian Neural Networks: Review and Debates Federico Danieli Konstantinos Pitas M. Vladimirova Vincent Fortuin BDL AAML 103 20 0 28 Sep 2023
On the different regimes of Stochastic Gradient Descent Antonio Sclocchi Matthieu Wyart 71 20 0 19 Sep 2023
MFRL-BI: Design of a Model-free Reinforcement Learning Process Control Scheme by Using Bayesian Inference Yanrong Li Juan Du Wei Jiang 32 1 0 17 Sep 2023