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Understanding Memorization from the Perspective of Optimization via Efficient Influence Estimation


Dec 16, 2021
Futong Liu, Tao Lin, Martin Jaggi


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Interpreting Language Models Through Knowledge Graph Extraction


Nov 16, 2021
Vinitra Swamy, Angelika Romanou, Martin Jaggi

* Published at NeurIPS 2021: eXplainable AI for Debugging and Diagnosis Workshop 

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Linear Speedup in Personalized Collaborative Learning


Nov 10, 2021
El Mahdi Chayti, Sai Praneeth Karimireddy, Sebastian U. Stich, Nicolas Flammarion, Martin Jaggi


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Optimal Model Averaging: Towards Personalized Collaborative Learning


Oct 25, 2021
Felix Grimberg, Mary-Anne Hartley, Sai P. Karimireddy, Martin Jaggi

* 9 pages (12 pages incl. references and appendix), 1 figure, Best Paper at International Workshop on Federated Learning for User Privacy and Data Confidentiality in Conjunction with ICML 2021 (FL-ICML'21) ( https://web.archive.org/web/20210908135923/http://federated-learning.org/fl-icml-2021/ICML\%202021\%20Best\%20Paper.pdf

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WAFFLE: Weighted Averaging for Personalized Federated Learning


Oct 13, 2021
Martin Beaussart, Felix Grimberg, Mary-Anne Hartley, Martin Jaggi

* Submitted to NeurIPS 2021 Workshop on New Frontiers in Federated Learning: Privacy, Fairness, Robustness, Personalization and Data Ownership 

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RelaySum for Decentralized Deep Learning on Heterogeneous Data


Oct 08, 2021
Thijs Vogels, Lie He, Anastasia Koloskova, Tao Lin, Sai Praneeth Karimireddy, Sebastian U. Stich, Martin Jaggi

* To appear in NeurIPS 2021 

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On Second-order Optimization Methods for Federated Learning


Sep 06, 2021
Sebastian Bischoff, Stephan GĂĽnnemann, Martin Jaggi, Sebastian U. Stich

* ICML 2021 Workshop "Beyond first-order methods in ML systems" 

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Semantic Perturbations with Normalizing Flows for Improved Generalization


Aug 18, 2021
Oguz Kaan Yuksel, Sebastian U. Stich, Martin Jaggi, Tatjana Chavdarova

* In Proceedings of the IEEE International Conference on Computer Vision 

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A Field Guide to Federated Optimization


Jul 14, 2021
Jianyu Wang, Zachary Charles, Zheng Xu, Gauri Joshi, H. Brendan McMahan, Blaise Aguera y Arcas, Maruan Al-Shedivat, Galen Andrew, Salman Avestimehr, Katharine Daly, Deepesh Data, Suhas Diggavi, Hubert Eichner, Advait Gadhikar, Zachary Garrett, Antonious M. Girgis, Filip Hanzely, Andrew Hard, Chaoyang He, Samuel Horvath, Zhouyuan Huo, Alex Ingerman, Martin Jaggi, Tara Javidi, Peter Kairouz, Satyen Kale, Sai Praneeth Karimireddy, Jakub Konecny, Sanmi Koyejo, Tian Li, Luyang Liu, Mehryar Mohri, Hang Qi, Sashank J. Reddi, Peter Richtarik, Karan Singhal, Virginia Smith, Mahdi Soltanolkotabi, Weikang Song, Ananda Theertha Suresh, Sebastian U. Stich, Ameet Talwalkar, Hongyi Wang, Blake Woodworth, Shanshan Wu, Felix X. Yu, Honglin Yuan, Manzil Zaheer, Mi Zhang, Tong Zhang, Chunxiang Zheng, Chen Zhu, Wennan Zhu


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IFedAvg: Interpretable Data-Interoperability for Federated Learning


Jul 14, 2021
David Roschewitz, Mary-Anne Hartley, Luca Corinzia, Martin Jaggi


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Implicit Gradient Alignment in Distributed and Federated Learning


Jun 25, 2021
Yatin Dandi, Luis Barba, Martin Jaggi


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Simultaneous Training of Partially Masked Neural Networks


Jun 16, 2021
Amirkeivan Mohtashami, Martin Jaggi, Sebastian U. Stich


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Lightweight Cross-Lingual Sentence Representation Learning


Jun 12, 2021
Zhuoyuan Mao, Prakhar Gupta, Chenhui Chu, Martin Jaggi, Sadao Kurohashi

* ACL 2021 

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Obtaining Better Static Word Embeddings Using Contextual Embedding Models


Jun 08, 2021
Prakhar Gupta, Martin Jaggi

* ACL 2021 accept 

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Federated Learning for Malware Detection in IoT Devices


Apr 15, 2021
Valerian Rey, Pedro Miguel Sánchez Sánchez, Alberto Huertas Celdrán, Gérôme Bovet, Martin Jaggi


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Critical Parameters for Scalable Distributed Learning with Large Batches and Asynchronous Updates


Mar 03, 2021
Sebastian U. Stich, Amirkeivan Mohtashami, Martin Jaggi

* Proceedings of the 24th International Conference on Artificial Intelligence and Statistics (AISTATS) 2021 

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Consensus Control for Decentralized Deep Learning


Feb 09, 2021
Lingjing Kong, Tao Lin, Anastasia Koloskova, Martin Jaggi, Sebastian U. Stich

* LK and TL contribute equally 

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Quasi-Global Momentum: Accelerating Decentralized Deep Learning on Heterogeneous Data


Feb 09, 2021
Tao Lin, Sai Praneeth Karimireddy, Sebastian U. Stich, Martin Jaggi


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Exact Optimization of Conformal Predictors via Incremental and Decremental Learning


Feb 05, 2021
Giovanni Cherubin, Konstantinos Chatzikokolakis, Martin Jaggi


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Learning from History for Byzantine Robust Optimization


Dec 18, 2020
Sai Praneeth Karimireddy, Lie He, Martin Jaggi

* 22 pages, 5 figures 

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A Linearly Convergent Algorithm for Decentralized Optimization: Sending Less Bits for Free!


Nov 03, 2020
Dmitry Kovalev, Anastasia Koloskova, Martin Jaggi, Peter Richtarik, Sebastian U. Stich


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Sparse Communication for Training Deep Networks


Sep 19, 2020
Negar Foroutan Eghlidi, Martin Jaggi


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Mime: Mimicking Centralized Stochastic Algorithms in Federated Learning


Aug 08, 2020
Sai Praneeth Karimireddy, Martin Jaggi, Satyen Kale, Mehryar Mohri, Sashank J. Reddi, Sebastian U. Stich, Ananda Theertha Suresh


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PowerGossip: Practical Low-Rank Communication Compression in Decentralized Deep Learning


Aug 04, 2020
Thijs Vogels, Sai Praneeth Karimireddy, Martin Jaggi


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Multi-Head Attention: Collaborate Instead of Concatenate


Jun 29, 2020
Jean-Baptiste Cordonnier, Andreas Loukas, Martin Jaggi


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Taming GANs with Lookahead


Jun 25, 2020
Tatjana Chavdarova, Matteo Pagliardini, Martin Jaggi, Francois Fleuret


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Byzantine-Robust Learning on Heterogeneous Datasets via Resampling


Jun 23, 2020
Lie He, Sai Praneeth Karimireddy, Martin Jaggi


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Dynamic Model Pruning with Feedback


Jun 12, 2020
Tao Lin, Sebastian U. Stich, Luis Barba, Daniil Dmitriev, Martin Jaggi

* appearing at ICLR 2020 

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