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Averaging Weights Leads to Wider Optima and Better Generalization

14 March 2018

Dmitry Vetrov

Papers citing "Averaging Weights Leads to Wider Optima and Better Generalization"

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Title
Adversarial Training with Stochastic Weight Average Joong-won Hwang Youngwan Lee Sungchan Oh Yuseok Bae OOD AAML 65 11 0 21 Sep 2020
Kaggle forecasting competitions: An overlooked learning opportunity Casper Solheim Bojer Jens Peder Meldgaard AI4TS 84 212 0 16 Sep 2020
Extending Label Smoothing Regularization with Self-Knowledge Distillation Jiyue Wang Pei Zhang Wenjie Pang Jie Li 21 0 0 11 Sep 2020
Going deeper with brain morphometry using neural networks Rodrigo Santa Cruz Leo Lebrat Pierrick Bourgeat Vincent Doré Jason Dowling Jurgen Fripp Clinton Fookes Olivier Salvado 3DV MedIm 31 6 0 07 Sep 2020
The 2ST-UNet for Pneumothorax Segmentation in Chest X-Rays using ResNet34 as a Backbone for U-Net Ayat Abedalla Malak Abdullah M. Al-Ayyoub E. Benkhelifa 44 13 0 06 Sep 2020
FedBE: Making Bayesian Model Ensemble Applicable to Federated Learning Hong-You Chen Wei-Lun Chao FedML 98 262 0 04 Sep 2020
Ramifications of Approximate Posterior Inference for Bayesian Deep Learning in Adversarial and Out-of-Distribution Settings John Mitros A. Pakrashi Brian Mac Namee UQCV 98 2 0 03 Sep 2020
Action and Perception as Divergence Minimization Danijar Hafner Pedro A. Ortega Jimmy Ba Thomas Parr Karl J. Friston N. Heess 91 53 0 03 Sep 2020
Robust, Accurate Stochastic Optimization for Variational Inference Akash Kumar Dhaka Alejandro Catalina Michael Riis Andersen Maans Magnusson Jonathan H. Huggins Aki Vehtari 71 34 0 01 Sep 2020
VarifocalNet: An IoU-aware Dense Object Detector Haoyang Zhang Ying Wang Feras Dayoub Niko Sünderhauf ObjD 128 695 0 31 Aug 2020
MTOP: A Comprehensive Multilingual Task-Oriented Semantic Parsing Benchmark Haoran Li Abhinav Arora Shuohui Chen Anchit Gupta Sonal Gupta Yashar Mehdad 129 180 0 21 Aug 2020
Obtaining Adjustable Regularization for Free via Iterate Averaging Jingfeng Wu Vladimir Braverman Lin F. Yang 63 2 0 15 Aug 2020
A community-powered search of machine learning strategy space to find NMR property prediction models Lars A. Bratholm W. Gerrard Brandon M. Anderson Shaojie Bai Sunghwan Choi ... A. Torrubia Devin Willmott C. Butts David R. Glowacki Kaggle participants 46 17 0 13 Aug 2020
Unifying supervised learning and VAEs -- coverage, systematics and goodness-of-fit in normalizing-flow based neural network models for astro-particle reconstructions T. Glüsenkamp 39 1 0 13 Aug 2020
An Ensemble of Simple Convolutional Neural Network Models for MNIST Digit Recognition Sanghyeon An Min Jun Lee Sanglee Park H. Yang Jungmin So 87 79 0 12 Aug 2020
PROFIT: A Novel Training Method for sub-4-bit MobileNet Models Eunhyeok Park S. Yoo MQ 59 85 0 11 Aug 2020
Low-loss connection of weight vectors: distribution-based approaches Ivan Anokhin Dmitry Yarotsky 3DV 107 4 0 03 Aug 2020
MLR-SNet: Transferable LR Schedules for Heterogeneous Tasks Jun Shu Yanwen Zhu Qian Zhao Zongben Xu Deyu Meng 75 7 0 29 Jul 2020
Neural networks with late-phase weights J. Oswald Seijin Kobayashi Alexander Meulemans Christian Henning Benjamin Grewe João Sacramento 94 35 0 25 Jul 2020
Word Embeddings: Stability and Semantic Change Lucas Rettenmeier BDL 34 1 0 23 Jul 2020
Data-Efficient Ranking Distillation for Image Retrieval Zakaria Laskar Arno Solin VLM 28 4 0 10 Jul 2020
DS-Sync: Addressing Network Bottlenecks with Divide-and-Shuffle Synchronization for Distributed DNN Training Weiyan Wang Cengguang Zhang Liu Yang Kai Chen Kun Tan 75 12 0 07 Jul 2020
Balanced Symmetric Cross Entropy for Large Scale Imbalanced and Noisy Data Feifei Huang Jie Li Xuelin Zhu 20 10 0 03 Jul 2020
Descending through a Crowded Valley - Benchmarking Deep Learning Optimizers Robin M. Schmidt Frank Schneider Philipp Hennig ODL 217 168 0 03 Jul 2020
DHARI Report to EPIC-Kitchens 2020 Object Detection Challenge Kaide Li Bingyan Liao Laifeng Hu Yaonong Wang 44 0 0 28 Jun 2020
Smooth Adversarial Training Cihang Xie Mingxing Tan Boqing Gong Alan Yuille Quoc V. Le OOD 94 154 0 25 Jun 2020
Collective Learning by Ensembles of Altruistic Diversifying Neural Networks Benjamin Brazowski E. Schneidman FedML 43 4 0 20 Jun 2020
Directional Pruning of Deep Neural Networks Shih-Kang Chao Zhanyu Wang Yue Xing Guang Cheng ODL 76 33 0 16 Jun 2020
Learning Rates as a Function of Batch Size: A Random Matrix Theory Approach to Neural Network Training Diego Granziol S. Zohren Stephen J. Roberts ODL 148 50 0 16 Jun 2020
Flatness is a False Friend Diego Granziol ODL 59 19 0 16 Jun 2020
Calibrating Deep Neural Network Classifiers on Out-of-Distribution Datasets Zhihui Shao Jianyi Yang Shaolei Ren OODD 72 11 0 16 Jun 2020
Beyond Random Matrix Theory for Deep Networks Diego Granziol 123 16 0 13 Jun 2020
Mean-Field Approximation to Gaussian-Softmax Integral with Application to Uncertainty Estimation Zhiyun Lu Eugene Ie Fei Sha UQCV BDL 68 14 0 13 Jun 2020
Hindsight Logging for Model Training Rolando Garcia Eric Liu Vikram Sreekanti Bobby Yan Anusha Dandamudi Joseph E. Gonzalez J. M. Hellerstein Koushik Sen VLM 77 10 0 12 Jun 2020
Ensemble Distillation for Robust Model Fusion in Federated Learning Tao R. Lin Lingjing Kong Sebastian U. Stich Martin Jaggi FedML 141 1,060 0 12 Jun 2020
A benchmark study on reliable molecular supervised learning via Bayesian learning Doyeong Hwang Grace Lee Hanseok Jo Seyoul Yoon Seongok Ryu 84 9 0 12 Jun 2020
An Overview of Deep Semi-Supervised Learning Yassine Ouali C´eline Hudelot Myriam Tami SSL HAI 131 303 0 09 Jun 2020
Detection of prostate cancer in whole-slide images through end-to-end training with image-level labels H. Pinckaers W. Bulten J. A. van der Laak G. Litjens MedIm 84 73 0 05 Jun 2020
Pathological myopia classification with simultaneous lesion segmentation using deep learning Ruben Hemelings B. Elen Matthew B. Blaschko J. Jacob Ingeborg Stalmans P. Boever 43 52 0 04 Jun 2020
One Versus all for deep Neural Network Incertitude (OVNNI) quantification Gianni Franchi Andrei Bursuc Emanuel Aldea Séverine Dubuisson Isabelle Bloch UQCV BDL 66 22 0 01 Jun 2020
CoolMomentum: A Method for Stochastic Optimization by Langevin Dynamics with Simulated Annealing O. Borysenko M. Byshkin ODL 60 14 0 29 May 2020
Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors Michael W. Dusenberry Ghassen Jerfel Yeming Wen Yi-An Ma Jasper Snoek Katherine A. Heller Balaji Lakshminarayanan Dustin Tran UQCV BDL 105 215 0 14 May 2020
Climate Adaptation: Reliably Predicting from Imbalanced Satellite Data Ruchit Rawal Prabhu Pradhan 40 1 0 26 Apr 2020
Local Search is a Remarkably Strong Baseline for Neural Architecture Search T. D. Ottelander A. Dushatskiy M. Virgolin Peter A. N. Bosman OOD 82 38 0 20 Apr 2020
DMT: Dynamic Mutual Training for Semi-Supervised Learning Zhengyang Feng Qianyu Zhou Qiqi Gu Xin Tan Guangliang Cheng Xuequan Lu Jianping Shi Lizhuang Ma 46 173 0 18 Apr 2020
Detached Error Feedback for Distributed SGD with Random Sparsification An Xu Heng-Chiao Huang 71 9 0 11 Apr 2020
Orthogonal Over-Parameterized Training Weiyang Liu Rongmei Lin Zhen Liu James M. Rehg Liam Paull Li Xiong Le Song Adrian Weller 82 45 0 09 Apr 2020
Gradient-based Data Augmentation for Semi-Supervised Learning H. Kaizuka 35 2 0 28 Mar 2020
Safe Crossover of Neural Networks Through Neuron Alignment Thomas Uriot Dario Izzo 77 14 0 23 Mar 2020
SAT: Improving Adversarial Training via Curriculum-Based Loss Smoothing Chawin Sitawarin S. Chakraborty David Wagner AAML 74 40 0 18 Mar 2020