Federated Gaussian Process: Convergence, Automatic Personalization and Multi-fidelity Modeling

28 November 2021

Papers citing "Federated Gaussian Process: Convergence, Automatic Personalization and Multi-fidelity Modeling"

46 / 46 papers shown

Title
The Internet of Federated Things (IoFT): A Vision for the Future and In-depth Survey of Data-driven Approaches for Federated Learning Raed Al Kontar Naichen Shi Xubo Yue Seokhyun Chung E. Byon ... Chinedum Okwudire Garvesh Raskutti R. Saigal Karandeep Singh Ye Zhisheng FedML 101 51 0 09 Nov 2021
Improving Fairness via Federated Learning Yuchen Zeng Hongxu Chen Kangwook Lee FedML 65 63 0 29 Oct 2021
Modular Gaussian Processes for Transfer Learning P. Moreno-Muñoz Antonio Artés-Rodríguez Mauricio A. Alvarez 30 4 0 26 Oct 2021
Fed-ensemble: Improving Generalization through Model Ensembling in Federated Learning Naichen Shi Fan Lai Raed Al Kontar Mosharaf Chowdhury FedML 74 36 0 21 Jul 2021
Recent Advances in Data-Driven Wireless Communication Using Gaussian Processes: A Comprehensive Survey Kai Chen Qinglei Kong Yijue Dai Yue Xu Feng Yin Lexi Xu Shuguang Cui 74 30 0 18 Mar 2021
Design and Analysis of Uplink and Downlink Communications for Federated Learning Sihui Zheng Cong Shen Xiang Chen 67 145 0 07 Dec 2020
Attack of the Tails: Yes, You Really Can Backdoor Federated Learning Hongyi Wang Kartik K. Sreenivasan Shashank Rajput Harit Vishwakarma Saurabh Agarwal Jy-yong Sohn Kangwook Lee Dimitris Papailiopoulos FedML 76 605 0 09 Jul 2020
Overview of Gaussian process based multi-fidelity techniques with variable relationship between fidelities Loïc Brevault M. Balesdent Ali Hebbal 46 71 0 30 Jun 2020
Federated Accelerated Stochastic Gradient Descent Honglin Yuan Tengyu Ma FedML 62 180 0 16 Jun 2020
Personalized Federated Learning with Moreau Envelopes Canh T. Dinh N. H. Tran Tuan Dung Nguyen FedML 87 996 0 16 Jun 2020
FedSplit: An algorithmic framework for fast federated optimization Reese Pathak Martin J. Wainwright FedML 212 184 0 11 May 2020
Inverting Gradients -- How easy is it to break privacy in federated learning? Jonas Geiping Hartmut Bauermeister Hannah Dröge Michael Moeller FedML 100 1,223 0 31 Mar 2020
Federated Learning with Matched Averaging Hongyi Wang Mikhail Yurochkin Yuekai Sun Dimitris Papailiopoulos Y. Khazaeni FedML 121 1,122 0 15 Feb 2020
Think Locally, Act Globally: Federated Learning with Local and Global Representations Paul Pu Liang Terrance Liu Liu Ziyin Nicholas B. Allen Randy P. Auerbach David Brent Ruslan Salakhutdinov Louis-Philippe Morency FedML 110 562 0 06 Jan 2020
Heterogeneity-aware and communication-efficient distributed statistical inference R. Duan Y. Ning Yong Chen 40 70 0 20 Dec 2019
Federated Learning with Personalization Layers Manoj Ghuhan Arivazhagan V. Aggarwal Aaditya Kumar Singh Sunav Choudhary FedML 87 840 0 02 Dec 2019
Why Non-myopic Bayesian Optimization is Promising and How Far Should We Look-ahead? A Study via Rollout Xubo Yue Raed Al Kontar 57 38 0 04 Nov 2019
BINOCULARS for Efficient, Nonmyopic Sequential Experimental Design Shali Jiang Henry Chai Javier I. González Roman Garnett OffRL 68 50 0 10 Sep 2019
Federated Learning: Challenges, Methods, and Future Directions Tian Li Anit Kumar Sahu Ameet Talwalkar Virginia Smith FedML 121 4,514 0 21 Aug 2019
On the Convergence of FedAvg on Non-IID Data Xiang Li Kaixuan Huang Wenhao Yang Shusen Wang Zhihua Zhang FedML 138 2,333 0 04 Jul 2019
Communication-Efficient Accurate Statistical Estimation Jianqing Fan Yongyi Guo Kaizheng Wang 41 114 0 12 Jun 2019
Fair Resource Allocation in Federated Learning Tian Li Maziar Sanjabi Ahmad Beirami Virginia Smith FedML 175 801 0 25 May 2019
Deep Gaussian Processes for Multi-fidelity Modeling Kurt Cutajar Mark Pullin Andreas C. Damianou Neil D. Lawrence Javier I. González AI4CE 53 110 0 18 Mar 2019
Agnostic Federated Learning M. Mohri Gary Sivek A. Suresh FedML 127 934 0 01 Feb 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
Analyzing Federated Learning through an Adversarial Lens A. Bhagoji Supriyo Chakraborty Prateek Mittal S. Calo FedML 280 1,054 0 29 Nov 2018
First-order Newton-type Estimator for Distributed Estimation and Inference Xi Chen Weidong Liu Yichen Zhang 75 51 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 48 56 0 27 Nov 2018
Quantile Regression Under Memory Constraint Xi Chen Weidong Liu Yichen Zhang 77 119 0 18 Oct 2018
Survey of multifidelity methods in uncertainty propagation, inference, and optimization Benjamin Peherstorfer Karen E. Willcox M. Gunzburger AI4CE 35 754 0 28 Jun 2018
Federated Multi-Task Learning Virginia Smith Chao-Kai Chiang Maziar Sanjabi Ameet Talwalkar FedML 150 1,808 0 30 May 2017
Learning of Gaussian Processes in Distributed and Communication Limited Systems Mostafa Tavassolipour S. Motahari M. Manzuri-Shalmani 27 22 0 07 May 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 357 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
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 421 2,937 0 15 Sep 2016
Distributed learning with regularized least squares Shaobo Lin Xin Guo Ding-Xuan Zhou 149 191 0 11 Aug 2016
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 397 17,468 0 17 Feb 2016
Gaussian Processes for Data-Efficient Learning in Robotics and Control M. Deisenroth Dieter Fox C. Rasmussen 109 693 0 10 Feb 2015
Distributed Gaussian Processes M. Deisenroth Jun Wei Ng GP 68 341 0 10 Feb 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.8K 150,039 0 22 Dec 2014
Hierarchical Mixture-of-Experts Model for Large-Scale Gaussian Process Regression Jun Wei Ng M. Deisenroth 55 51 0 09 Dec 2014
Generalized Product of Experts for Automatic and Principled Fusion of Gaussian Process Predictions Yanshuai Cao David J. Fleet 44 186 0 28 Oct 2014
Parallelizing MCMC via Weierstrass Sampler Xiangyu Wang David B. Dunson 91 138 0 17 Dec 2013
Gaussian Processes for Big Data J. Hensman Nicolò Fusi Neil D. Lawrence GP 104 1,230 0 26 Sep 2013
Deep Gaussian Processes Andreas C. Damianou Neil D. Lawrence GP BDL 127 1,181 0 02 Nov 2012
Gaussian process single-index models as emulators for computer experiments R. Gramacy H. Lian 81 89 0 22 Sep 2010