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Incentivizing Honesty among Competitors in Collaborative Learning and Optimization

25 May 2023

Martin Vechev

Papers citing "Incentivizing Honesty among Competitors in Collaborative Learning and Optimization"

24 / 24 papers shown

Title
Scalable Decentralized Algorithms for Online Personalized Mean Estimation Franco Galante Giovanni Neglia Emilio Leonardi FedML 136 1 0 20 Feb 2025
FL Games: A Federated Learning Framework for Distribution Shifts Sharut Gupta Kartik Ahuja Mohammad Havaei N. Chatterjee Yoshua Bengio OOD FedML 76 18 0 31 Oct 2022
Mechanisms that Incentivize Data Sharing in Federated Learning Sai Praneeth Karimireddy Wenshuo Guo Michael I. Jordan FedML 76 50 0 10 Jul 2022
Maximizing Global Model Appeal in Federated Learning Yae Jee Cho Divyansh Jhunjhunwala Tian Li Virginia Smith Gauri Joshi FedML 47 7 0 30 May 2022
Incentive Mechanisms for Federated Learning: From Economic and Game Theoretic Perspective Xuezhen Tu Kun Zhu Nguyen Cong Luong Dusit Niyato Yang Zhang Juan Li FedML AI4CE 75 122 0 20 Nov 2021
Linear Speedup in Personalized Collaborative Learning El Mahdi Chayti Sai Praneeth Karimireddy Sebastian U. Stich Nicolas Flammarion Martin Jaggi FedML 68 13 0 10 Nov 2021
Optimal Model Averaging: Towards Personalized Collaborative Learning Felix Grimberg Mary-Anne Hartley Sai Praneeth Karimireddy Martin Jaggi FedML MoMe 47 15 0 25 Oct 2021
Back to the Drawing Board: A Critical Evaluation of Poisoning Attacks on Production Federated Learning Virat Shejwalkar Amir Houmansadr Peter Kairouz Daniel Ramage AAML 103 219 0 23 Aug 2021
Optimality and Stability in Federated Learning: A Game-theoretic Approach Kate Donahue Jon M. Kleinberg FedML 58 48 0 17 Jun 2021
Mitigating Bias in Federated Learning Annie Abay Yi Zhou Nathalie Baracaldo Shashank Rajamoni Ebube Chuba Heiko Ludwig AI4CE 61 94 0 04 Dec 2020
Model-sharing Games: Analyzing Federated Learning Under Voluntary Participation Kate Donahue Jon M. Kleinberg FedML 74 82 0 02 Oct 2020
Data Poisoning Attacks Against Federated Learning Systems Vale Tolpegin Stacey Truex Mehmet Emre Gursoy Ling Liu FedML 118 660 0 16 Jul 2020
On the Sample Complexity of Adversarial Multi-Source PAC Learning Nikola Konstantinov Elias Frantar Dan Alistarh Christoph H. Lampert 42 18 0 24 Feb 2020
Advances and Open Problems in Federated Learning Peter Kairouz H. B. McMahan Brendan Avent A. Bellet M. Bennis ... Zheng Xu Qiang Yang Felix X. Yu Han Yu Sen Zhao FedML AI4CE 273 6,294 0 10 Dec 2019
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 547 42,639 0 03 Dec 2019
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 158 1,423 0 03 Dec 2018
Byzantine Stochastic Gradient Descent Dan Alistarh Zeyuan Allen-Zhu Jingkai Li FedML 73 297 0 23 Mar 2018
Byzantine-Robust Distributed Learning: Towards Optimal Statistical Rates Dong Yin Yudong Chen Kannan Ramchandran Peter L. Bartlett OOD FedML 127 1,517 0 05 Mar 2018
Learning Discrete Distributions from Untrusted Batches Mingda Qiao Gregory Valiant FedML 66 34 0 22 Nov 2017
Optimization Methods for Large-Scale Machine Learning Léon Bottou Frank E. Curtis J. Nocedal 252 3,225 0 15 Jun 2016
Robust Estimators in High Dimensions without the Computational Intractability Ilias Diakonikolas Gautam Kamath D. Kane Jingkai Li Ankur Moitra Alistair Stewart 73 513 0 21 Apr 2016
Communication-Efficient Learning of Deep Networks from Decentralized Data H. B. McMahan Eider Moore Daniel Ramage S. Hampson Blaise Agüera y Arcas FedML 408 17,593 0 17 Feb 2016
Optimum Statistical Estimation with Strategic Data Sources Yang Cai C. Daskalakis Christos H. Papadimitriou 103 140 0 11 Aug 2014
Making Gradient Descent Optimal for Strongly Convex Stochastic Optimization Alexander Rakhlin Ohad Shamir Karthik Sridharan 178 769 0 26 Sep 2011