Variational Federated Multi-Task Learning

14 June 2019

Papers citing "Variational Federated Multi-Task Learning"

33 / 33 papers shown

Title
Personalized Federated Learning of Probabilistic Models: A PAC-Bayesian Approach Mahrokh Ghoddousi Boroujeni Andreas Krause Giancarlo Ferrari-Trecate FedML 98 3 0 16 Jan 2024
Knowledge transfer in deep block-modular neural networks A. Terekhov Guglielmo Montone J. O'Regan 46 73 0 24 Jul 2019
Federated Collaborative Filtering for Privacy-Preserving Personalized Recommendation System Muhammad Ammad-ud-din E. Ivannikova Suleiman A. Khan Were Oyomno Qiang Fu K. E. Tan Adrian Flanagan FedML 68 271 0 29 Jan 2019
Federated Optimization in Heterogeneous Networks Tian Li Anit Kumar Sahu Manzil Zaheer Maziar Sanjabi Ameet Talwalkar Virginia Smith FedML 180 5,176 0 14 Dec 2018
Applied Federated Learning: Improving Google Keyboard Query Suggestions Timothy Yang Galen Andrew Hubert Eichner Haicheng Sun Wei Li Nicholas Kong Daniel Ramage F. Beaufays FedML 87 623 0 07 Dec 2018
LEAF: A Benchmark for Federated Settings S. Caldas Sai Meher Karthik Duddu Peter Wu Tian Li Jakub Konecný H. B. McMahan Virginia Smith Ameet Talwalkar FedML 134 1,419 0 03 Dec 2018
Communication-Efficient On-Device Machine Learning: Federated Distillation and Augmentation under Non-IID Private Data Eunjeong Jeong Seungeun Oh Hyesung Kim Jihong Park M. Bennis Seong-Lyun Kim FedML 88 603 0 28 Nov 2018
Partitioned Variational Inference: A unified framework encompassing federated and continual learning T. Bui Cuong V Nguyen S. Swaroop Richard Turner FedML 46 56 0 27 Nov 2018
Memory Replay GANs: learning to generate images from new categories without forgetting Chenshen Wu Luis Herranz Xialei Liu Yaxing Wang Joost van de Weijer Bogdan Raducanu CLL VLM GAN 49 195 0 06 Sep 2018
Federated Learning with Non-IID Data Yue Zhao Meng Li Liangzhen Lai Naveen Suda Damon Civin Vikas Chandra FedML 152 2,568 0 02 Jun 2018
Progress & Compress: A scalable framework for continual learning Jonathan Richard Schwarz Jelena Luketina Wojciech M. Czarnecki A. Grabska-Barwinska Yee Whye Teh Razvan Pascanu R. Hadsell CLL 120 888 0 16 May 2018
Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches Yeming Wen Paul Vicol Jimmy Ba Dustin Tran Roger C. Grosse BDL 47 311 0 12 Mar 2018
TensorFlow Distributions Joshua V. Dillon I. Langmore Dustin Tran E. Brevdo Srinivas Vasudevan David A. Moore Brian Patton Alexander A. Alemi Matt Hoffman Rif A. Saurous GP 96 351 0 28 Nov 2017
Variational Continual Learning Cuong V Nguyen Yingzhen Li T. Bui Richard Turner CLL VLM BDL 79 732 0 29 Oct 2017
An Overview of Multi-Task Learning in Deep Neural Networks Sebastian Ruder CVBM 146 2,826 0 15 Jun 2017
Federated Multi-Task Learning Virginia Smith Chao-Kai Chiang Maziar Sanjabi Ameet Talwalkar FedML 150 1,808 0 30 May 2017
Overcoming Catastrophic Forgetting by Incremental Moment Matching Sang-Woo Lee Jin-Hwa Kim Jaehyun Jun Jung-Woo Ha Byoung-Tak Zhang CLL 70 676 0 24 Mar 2017
EMNIST: an extension of MNIST to handwritten letters Gregory Cohen Saeed Afshar J. Tapson André van Schaik 63 720 0 17 Feb 2017
Overcoming catastrophic forgetting in neural networks J. Kirkpatrick Razvan Pascanu Neil C. Rabinowitz J. Veness Guillaume Desjardins ... A. Grabska-Barwinska Demis Hassabis Claudia Clopath D. Kumaran R. Hadsell CLL 354 7,504 0 02 Dec 2016
CoCoA: A General Framework for Communication-Efficient Distributed Optimization Virginia Smith Simone Forte Chenxin Ma Martin Takáč Michael I. Jordan Martin Jaggi 68 273 0 07 Nov 2016
Federated Optimization: Distributed Machine Learning for On-Device Intelligence Jakub Konecný H. B. McMahan Daniel Ramage Peter Richtárik FedML 126 1,897 0 08 Oct 2016
Progressive Neural Networks Andrei A. Rusu Neil C. Rabinowitz Guillaume Desjardins Hubert Soyer J. Kirkpatrick Koray Kavukcuoglu Razvan Pascanu R. Hadsell CLL AI4CE 77 2,446 0 15 Jun 2016
TensorFlow: A system for large-scale machine learning Martín Abadi P. Barham Jianmin Chen Zhiwen Chen Andy Davis ... Vijay Vasudevan Pete Warden Martin Wicke Yuan Yu Xiaoqiang Zhang GNN AI4CE 429 18,350 0 27 May 2016
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 394 17,453 0 17 Feb 2016
Distilling the Knowledge in a Neural Network Geoffrey E. Hinton Oriol Vinyals J. Dean FedML 344 19,634 0 09 Mar 2015
Adding vs. Averaging in Distributed Primal-Dual Optimization Chenxin Ma Virginia Smith Martin Jaggi Michael I. Jordan Peter Richtárik Martin Takáč FedML 94 177 0 12 Feb 2015
Deep learning with Elastic Averaging SGD Sixin Zhang A. Choromańska Yann LeCun FedML 96 610 0 20 Dec 2014
Parallel training of DNNs with Natural Gradient and Parameter Averaging Daniel Povey Xiaohui Zhang Sanjeev Khudanpur FedML 83 251 0 27 Oct 2014
Communication-Efficient Distributed Dual Coordinate Ascent Martin Jaggi Virginia Smith Martin Takáč Jonathan Terhorst S. Krishnan Thomas Hofmann Michael I. Jordan 84 353 0 04 Sep 2014
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 450 16,940 0 20 Dec 2013
Network In Network Min Lin Qiang Chen Shuicheng Yan 291 6,274 0 16 Dec 2013
Streaming Variational Bayes Tamara Broderick N. Boyd Andre Wibisono Ashia Wilson Michael I. Jordan 80 345 0 25 Jul 2013
Expectation Propagation for approximate Bayesian inference T. Minka 127 1,907 0 10 Jan 2013