AdaBest: Minimizing Client Drift in Federated Learning via Adaptive Bias Estimation (English)
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In:
Computer Vision – ECCV 2022
: 17th European Conference, Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part XXIII
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Chapter: 41
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710-726
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2022
- Article/Chapter (Book) / Electronic Resource
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Title:AdaBest: Minimizing Client Drift in Federated Learning via Adaptive Bias Estimation
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Additional title:Lect.Notes Computer
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Contributors:Avidan, Shai ( editor ) / Brostow, Gabriel ( editor ) / Cissé, Moustapha ( editor ) / Farinella, Giovanni Maria ( editor ) / Hassner, Tal ( editor ) / Varno, Farshid ( author ) / Saghayi, Marzie ( author ) / Rafiee Sevyeri, Laya ( author ) / Gupta, Sharut ( author ) / Matwin, Stan ( author )
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Conference:European Conference on Computer Vision ; 2022 ; Tel Aviv, Israel
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Published in:Computer Vision – ECCV 2022 : 17th European Conference, Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part XXIII ; Chapter: 41 ; 710-726Lecture Notes in Computer Science ; 13683 ; 710-726
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Publisher:
- New search for: Springer Nature Switzerland
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Place of publication:Cham
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Publication date:2022-10-28
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Size:17 pages
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ISBN:
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ISSN:
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DOI:
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Type of media:Article/Chapter (Book)
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Type of material:Electronic Resource
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Language:English
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Keywords:
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Source:
Table of contents eBook
The tables of contents are generated automatically and are based on the data records of the individual contributions available in the index of the TIB portal. The display of the Tables of Contents may therefore be incomplete.
- 1
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Accelerating Score-Based Generative Models with Preconditioned Diffusion SamplingMa, Hengyuan / Zhang, Li / Zhu, Xiatian / Feng, Jianfeng et al. | 2022
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Learning to Generate Realistic LiDAR Point CloudsZyrianov, Vlas / Zhu, Xiyue / Wang, Shenlong et al. | 2022
- 3
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RFNet-4D: Joint Object Reconstruction and Flow Estimation from 4D Point CloudsVu, Tuan-Anh / Nguyen, Duc Thanh / Hua, Binh-Son / Pham, Quang-Hieu / Yeung, Sai-Kit et al. | 2022
- 4
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Diverse Image Inpainting with Normalizing FlowWang, Cairong / Zhu, Yiming / Yuan, Chun et al. | 2022
- 5
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Improved Masked Image Generation with Token-CriticLezama, José / Chang, Huiwen / Jiang, Lu / Essa, Irfan et al. | 2022
- 6
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TREND: Truncated Generalized Normal Density Estimation of Inception Embeddings for GAN EvaluationLee, Junghyuk / Lee, Jong-Seok et al. | 2022
- 7
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Exploring Gradient-Based Multi-directional Controls in GANsChen, Zikun / Jiang, Ruowei / Duke, Brendan / Zhao, Han / Aarabi, Parham et al. | 2022
- 8
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Spatially Invariant Unsupervised 3D Object-Centric Learning and Scene DecompositionWang, Tianyu / Liu, Miaomiao / Ng, Kee Siong et al. | 2022
- 9
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Neural Scene Decoration from a Single PhotographPang, Hong-Wing / Chen, Yingshu / Le, Phuoc-Hieu / Hua, Binh-Son / Nguyen, Duc Thanh / Yeung, Sai-Kit et al. | 2022
- 10
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Outpainting by QueriesYao, Kai / Gao, Penglei / Yang, Xi / Sun, Jie / Zhang, Rui / Huang, Kaizhu et al. | 2022
- 11
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Unleashing Transformers: Parallel Token Prediction with Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized CodesBond-Taylor, Sam / Hessey, Peter / Sasaki, Hiroshi / Breckon, Toby P. / Willcocks, Chris G. et al. | 2022
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GAN Cocktail: Mixing GANs Without Dataset AccessAvrahami, Omri / Lischinski, Dani / Fried, Ohad et al. | 2022
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Controllable Shadow Generation Using Pixel Height MapsSheng, Yichen / Liu, Yifan / Zhang, Jianming / Yin, Wei / Oztireli, A. Cengiz / Zhang, He / Lin, Zhe / Shechtman, Eli / Benes, Bedrich et al. | 2022
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Learning Where to Look – Generative NAS is Surprisingly EfficientLukasik, Jovita / Jung, Steffen / Keuper, Margret et al. | 2022
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Subspace Diffusion Generative ModelsJing, Bowen / Corso, Gabriele / Berlinghieri, Renato / Jaakkola, Tommi et al. | 2022
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DuelGAN: A Duel Between Two Discriminators Stabilizes the GAN TrainingWei, Jiaheng / Liu, Minghao / Luo, Jiahao / Zhu, Andrew / Davis, James / Liu, Yang et al. | 2022
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MINER: Multiscale Implicit Neural RepresentationSaragadam, Vishwanath / Tan, Jasper / Balakrishnan, Guha / Baraniuk, Richard G. / Veeraraghavan, Ashok et al. | 2022
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An Embedded Feature Whitening Approach to Deep Neural Network OptimizationYong, Hongwei / Zhang, Lei et al. | 2022
- 21
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Q-FW: A Hybrid Classical-Quantum Frank-Wolfe for Quadratic Binary OptimizationYurtsever, Alp / Birdal, Tolga / Golyanik, Vladislav et al. | 2022
- 22
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Self-supervised Learning of Visual Graph MatchingLiu, Chang / Zhang, Shaofeng / Yang, Xiaokang / Yan, Junchi et al. | 2022
- 23
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Scalable Learning to Optimize: A Learned Optimizer Can Train Big ModelsChen, Xuxi / Chen, Tianlong / Cheng, Yu / Chen, Weizhu / Awadallah, Ahmed / Wang, Zhangyang et al. | 2022
- 24
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QISTA-ImageNet: A Deep Compressive Image Sensing Framework Solving \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\ell _q$$\end{document}-Norm Optimization ProblemLin, Gang-Xuan / Hu, Shih-Wei / Lu, Chun-Shien et al. | 2022
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R-DFCIL: Relation-Guided Representation Learning for Data-Free Class Incremental LearningGao, Qiankun / Zhao, Chen / Ghanem, Bernard / Zhang, Jian et al. | 2022
- 26
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Domain Generalization by Mutual-Information Regularization with Pre-trained ModelsCha, Junbum / Lee, Kyungjae / Park, Sungrae / Chun, Sanghyuk et al. | 2022
- 27
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Predicting Is Not Understanding: Recognizing and Addressing Underspecification in Machine LearningTeney, Damien / Peyrard, Maxime / Abbasnejad, Ehsan et al. | 2022
- 28
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Neural-Sim: Learning to Generate Training Data with NeRFGe, Yunhao / Behl, Harkirat / Xu, Jiashu / Gunasekar, Suriya / Joshi, Neel / Song, Yale / Wang, Xin / Itti, Laurent / Vineet, Vibhav et al. | 2022
- 29
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Bayesian Optimization with Clustering and Rollback for CNN Auto PruningFan, Hanwei / Mu, Jiandong / Zhang, Wei et al. | 2022
- 30
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Learned Variational Video Color PropagationHofinger, Markus / Kobler, Erich / Effland, Alexander / Pock, Thomas et al. | 2022
- 31
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Continual Variational Autoencoder Learning via Online Cooperative MemorizationYe, Fei / Bors, Adrian G. et al. | 2022
- 32
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Learning to Learn with Smooth RegularizationXiong, Yuanhao / Hsieh, Cho-Jui et al. | 2022
- 33
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Incremental Task Learning with Incremental Rank UpdatesHyder, Rakib / Shao, Ken / Hou, Boyu / Markopoulos, Panos / Prater-Bennette, Ashley / Asif, M. Salman et al. | 2022
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Batch-Efficient EigenDecomposition for Small and Medium MatricesSong, Yue / Sebe, Nicu / Wang, Wei et al. | 2022
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Ensemble Learning Priors Driven Deep Unfolding for Scalable Video Snapshot Compressive ImagingYang, Chengshuai / Zhang, Shiyu / Yuan, Xin et al. | 2022
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Approximate Discrete Optimal Transport Plan with Auxiliary Measure MethodAn, Dongsheng / Lei, Na / Gu, Xianfeng et al. | 2022
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A Comparative Study of Graph Matching Algorithms in Computer VisionHaller, Stefan / Feineis, Lorenz / Hutschenreiter, Lisa / Bernard, Florian / Rother, Carsten / Kainmüller, Dagmar / Swoboda, Paul / Savchynskyy, Bogdan et al. | 2022
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Improving Generalization in Federated Learning by Seeking Flat MinimaCaldarola, Debora / Caputo, Barbara / Ciccone, Marco et al. | 2022
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Semidefinite Relaxations of Truncated Least-Squares in Robust Rotation Search: Tight or NotPeng, Liangzu / Fazlyab, Mahyar / Vidal, René et al. | 2022
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Transfer Without ForgettingBoschini, Matteo / Bonicelli, Lorenzo / Porrello, Angelo / Bellitto, Giovanni / Pennisi, Matteo / Palazzo, Simone / Spampinato, Concetto / Calderara, Simone et al. | 2022
- 41
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AdaBest: Minimizing Client Drift in Federated Learning via Adaptive Bias EstimationVarno, Farshid / Saghayi, Marzie / Rafiee Sevyeri, Laya / Gupta, Sharut / Matwin, Stan / Havaei, Mohammad et al. | 2022
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Tackling Long-Tailed Category Distribution Under Domain ShiftsGu, Xiao / Guo, Yao / Li, Zeju / Qiu, Jianing / Dou, Qi / Liu, Yuxuan / Lo, Benny / Yang, Guang-Zhong et al. | 2022
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