More from the Same Authors

• 2021 : Interpreting Language Models Through Knowledge Graph Extraction »
  Vinitra Swamy · Angelika Romanou · Martin Jaggi
• 2021 : Understanding Memorization from the Perspective of Optimization via Efficient Influence Estimation »
  Futong Liu · Tao Lin · Martin Jaggi
• 2021 : Understanding Memorization from the Perspective of Optimization via Efficient Influence Estimation »
  Futong Liu · Tao Lin · Martin Jaggi
• 2021 : WAFFLE: Weighted Averaging for Personalized Federated Learning »
  Martin Beaussart · Mary-Anne Hartley · Martin Jaggi
• 2022 : Data-heterogeneity-aware Mixing for Decentralized Learning »
  Yatin Dandi · Anastasiia Koloskova · Martin Jaggi · Sebastian Stich
• 2022 : Decentralized Stochastic Optimization with Client Sampling »
  Ziwei Liu · Anastasiia Koloskova · Martin Jaggi · Tao Lin
• 2022 : Towards Provably Personalized Federated Learning via Threshold-Clustering of Similar Clients »
  Mariel A Werner · Lie He · Sai Praneeth Karimireddy · Michael Jordan · Martin Jaggi
• 2022 : Diversity through Disagreement for Better Transferability »
  Matteo Pagliardini · Martin Jaggi · François Fleuret · Sai Praneeth Karimireddy
• 2022 : Scalable Collaborative Learning via Representation Sharing »
  Frédéric Berdoz · Abhishek Singh · Martin Jaggi · Ramesh Raskar
• 2022 Poster: Sharper Convergence Guarantees for Asynchronous SGD for Distributed and Federated Learning »
  Anastasiia Koloskova · Sebastian Stich · Martin Jaggi
• 2022 Poster: FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings »
  Jean Ogier du Terrail · Samy-Safwan Ayed · Edwige Cyffers · Felix Grimberg · Chaoyang He · Regis Loeb · Paul Mangold · Tanguy Marchand · Othmane Marfoq · Erum Mushtaq · Boris Muzellec · Constantin Philippenko · Santiago Silva · Maria Teleńczuk · Shadi Albarqouni · Salman Avestimehr · Aurélien Bellet · Aymeric Dieuleveut · Martin Jaggi · Sai Praneeth Karimireddy · Marco Lorenzi · Giovanni Neglia · Marc Tommasi · Mathieu Andreux
• 2022 Poster: Beyond spectral gap: the role of the topology in decentralized learning »
  Thijs Vogels · Hadrien Hendrikx · Martin Jaggi
• 2021 : [S11] Interpreting Language Models Through Knowledge Graph Extraction »
  Vinitra Swamy · Angelika Romanou · Martin Jaggi
• 2021 : Learning with Strange Gradients, Martin Jaggi »
  Martin Jaggi
• 2021 Poster: Breaking the centralized barrier for cross-device federated learning »
  Sai Praneeth Karimireddy · Martin Jaggi · Satyen Kale · Mehryar Mohri · Sashank Reddi · Sebastian Stich · Ananda Theertha Suresh
• 2021 Poster: RelaySum for Decentralized Deep Learning on Heterogeneous Data »
  Thijs Vogels · Lie He · Anastasiia Koloskova · Sai Praneeth Karimireddy · Tao Lin · Sebastian Stich · Martin Jaggi
• 2020 Poster: Ensemble Distillation for Robust Model Fusion in Federated Learning »
  Tao Lin · Lingjing Kong · Sebastian Stich · Martin Jaggi
• 2020 Poster: Practical Low-Rank Communication Compression in Decentralized Deep Learning »
  Thijs Vogels · Sai Praneeth Karimireddy · Martin Jaggi
• 2020 Poster: Model Fusion via Optimal Transport »
  Sidak Pal Singh · Martin Jaggi
• 2019 Poster: PowerSGD: Practical Low-Rank Gradient Compression for Distributed Optimization »
  Thijs Vogels · Sai Praneeth Karimireddy · Martin Jaggi
• 2019 Poster: Unsupervised Scalable Representation Learning for Multivariate Time Series »
  Jean-Yves Franceschi · Aymeric Dieuleveut · Martin Jaggi
• 2018 Poster: COLA: Decentralized Linear Learning »
  Lie He · Yatao Bian · Martin Jaggi
• 2018 Poster: Sparsified SGD with Memory »
  Sebastian Stich · Jean-Baptiste Cordonnier · Martin Jaggi
• 2018 Poster: Training DNNs with Hybrid Block Floating Point »
  Mario Drumond · Tao Lin · Martin Jaggi · Babak Falsafi
• 2017 Poster: Safe Adaptive Importance Sampling »
  Sebastian Stich · Anant Raj · Martin Jaggi
• 2017 Spotlight: Safe Adaptive Importance Sampling »
  Sebastian Stich · Anant Raj · Martin Jaggi
• 2017 Poster: Greedy Algorithms for Cone Constrained Optimization with Convergence Guarantees »
  Francesco Locatello · Michael Tschannen · Gunnar Ratsch · Martin Jaggi
• 2017 Poster: Efficient Use of Limited-Memory Accelerators for Linear Learning on Heterogeneous Systems »
  Celestine Dünner · Thomas Parnell · Martin Jaggi
• 2015 Poster: On the Global Linear Convergence of Frank-Wolfe Optimization Variants »
  Simon Lacoste-Julien · Martin Jaggi
• 2014 Workshop: OPT2014: Optimization for Machine Learning »
  Zaid Harchaoui · Suvrit Sra · Alekh Agarwal · Martin Jaggi · Miro Dudik · Aaditya Ramdas · Jean Lasserre · Yoshua Bengio · Amir Beck
• 2014 Poster: Communication-Efficient Distributed Dual Coordinate Ascent »
  Martin Jaggi · Virginia Smith · Martin Takac · Jonathan Terhorst · Sanjay Krishnan · Thomas Hofmann · Michael Jordan
• 2013 Workshop: Greedy Algorithms, Frank-Wolfe and Friends - A modern perspective »
  Martin Jaggi · Zaid Harchaoui · Federico Pierucci