SAM as an Optimal Relaxation of Bayes

4 October 2022

Papers citing "SAM as an Optimal Relaxation of Bayes"

29 / 29 papers shown

Title
Uncertainty-Aware Decoding with Minimum Bayes Risk Nico Daheim Clara Meister Thomas Möllenhoff Iryna Gurevych 53 0 0 07 Mar 2025
Sharpness-Aware Black-Box Optimization Feiyang Ye Yueming Lyu Xuehao Wang Masashi Sugiyama Yu-Jie Zhang Ivor W. Tsang AAML 42 0 0 16 Oct 2024
Improving Generalization with Flat Hilbert Bayesian Inference Tuan Truong Quyen Tran Quan Pham-Ngoc Nhat Ho Dinh Q. Phung Trung Le 13 0 0 05 Oct 2024
Convergence of Sharpness-Aware Minimization Algorithms using Increasing Batch Size and Decaying Learning Rate Hinata Harada Hideaki Iiduka 28 1 0 16 Sep 2024
Improving SAM Requires Rethinking its Optimization Formulation Wanyun Xie Fabian Latorre Kimon Antonakopoulos Thomas Pethick V. Cevher 31 1 0 17 Jul 2024
Flat Posterior Does Matter For Bayesian Model Averaging Sungjun Lim Jeyoon Yeom Sooyon Kim Hoyoon Byun Jinho Kang Yohan Jung Jiyoung Jung Kyungwoo Song AAML BDL 40 0 0 21 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
Forget Sharpness: Perturbed Forgetting of Model Biases Within SAM Dynamics Ankit Vani Frederick Tung Gabriel L. Oliveira Hossein Sharifi-Noghabi AAML 31 0 0 10 Jun 2024
Flatness Improves Backbone Generalisation in Few-shot Classification Rui Li Martin Trapp Marcus Klasson Arno Solin 39 0 0 11 Apr 2024
Revisiting Random Weight Perturbation for Efficiently Improving Generalization Tao Li Qinghua Tao Weihao Yan Zehao Lei Yingwen Wu Kun Fang M. He Xiaolin Huang AAML 24 5 0 30 Mar 2024
Variational Learning is Effective for Large Deep Networks Yuesong Shen Nico Daheim Bai Cong Peter Nickl Gian Maria Marconi ... Rio Yokota Iryna Gurevych Daniel Cremers Mohammad Emtiyaz Khan Thomas Möllenhoff 30 22 0 27 Feb 2024
Momentum-SAM: Sharpness Aware Minimization without Computational Overhead Marlon Becker Frederick Altrock Benjamin Risse 74 5 0 22 Jan 2024
Entropy-MCMC: Sampling from Flat Basins with Ease Bolian Li Ruqi Zhang 17 5 0 09 Oct 2023
TRAM: Bridging Trust Regions and Sharpness Aware Minimization Tom Sherborne Naomi Saphra Pradeep Dasigi Hao Peng 25 4 0 05 Oct 2023
RSAM: Learning on manifolds with Riemannian Sharpness-aware Minimization Kenneth Allen Hoang-Phi Nguyen Tung Pham Ming-Jun Lai Mehrtash Harandi Dinh Q. Phung Trung Le AAML 17 2 0 29 Sep 2023
A Primer on Bayesian Neural Networks: Review and Debates Federico Danieli Konstantinos Pitas M. Vladimirova Vincent Fortuin BDL AAML 54 18 0 28 Sep 2023
Why Does Little Robustness Help? Understanding and Improving Adversarial Transferability from Surrogate Training Yechao Zhang Shengshan Hu Leo Yu Zhang Junyu Shi Minghui Li Xiaogeng Liu Wei Wan Hai Jin AAML 22 20 0 15 Jul 2023
The Interpolating Information Criterion for Overparameterized Models Liam Hodgkinson Christopher van der Heide Roberto Salomone Fred Roosta Michael W. Mahoney 16 7 0 15 Jul 2023
Practical Sharpness-Aware Minimization Cannot Converge All the Way to Optima Dongkuk Si Chulhee Yun 28 15 0 16 Jun 2023
Normalization Layers Are All That Sharpness-Aware Minimization Needs Maximilian Mueller Tiffany J. Vlaar David Rolnick Matthias Hein 8 18 0 07 Jun 2023
Optimal Transport Model Distributional Robustness Van-Anh Nguyen Trung Le Anh Tuan Bui Thanh-Toan Do Dinh Q. Phung OOD 22 3 0 07 Jun 2023
Decentralized SGD and Average-direction SAM are Asymptotically Equivalent Tongtian Zhu Fengxiang He Kaixuan Chen Mingli Song Dacheng Tao 34 15 0 05 Jun 2023
The Lie-Group Bayesian Learning Rule E. M. Kıral Thomas Möllenhoff Mohammad Emtiyaz Khan BDL 15 2 0 08 Mar 2023
Flat Seeking Bayesian Neural Networks Van-Anh Nguyen L. Vuong Hoang Phan Thanh-Toan Do Dinh Q. Phung Trung Le BDL 12 8 0 06 Feb 2023
Wide Mean-Field Bayesian Neural Networks Ignore the Data Beau Coker W. Bruinsma David R. Burt Weiwei Pan Finale Doshi-Velez UQCV BDL 32 22 0 23 Feb 2022
Sharpness-Aware Minimization Improves Language Model Generalization Dara Bahri H. Mobahi Yi Tay 119 97 0 16 Oct 2021
Lifting the Convex Conjugate in Lagrangian Relaxations: A Tractable Approach for Continuous Markov Random Fields Hartmut Bauermeister Emanuel Laude Thomas Möllenhoff Michael Moeller Daniel Cremers 17 9 0 13 Jul 2021
Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam Mohammad Emtiyaz Khan Didrik Nielsen Voot Tangkaratt Wu Lin Y. Gal Akash Srivastava ODL 74 266 0 13 Jun 2018
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 247 9,109 0 06 Jun 2015