Vogels, Thijs

10 publications

TMLR 2024 Exponential Moving Average of Weights in Deep Learning: Dynamics and Benefits Daniel Morales-Brotons, Thijs Vogels, Hadrien Hendrikx

ICML 2024 LASER: Linear Compression in Wireless Distributed Optimization Ashok Vardhan Makkuva, Marco Bondaschi, Thijs Vogels, Martin Jaggi, Hyeji Kim, Michael Gastpar

JMLR 2023 Beyond Spectral Gap: The Role of the Topology in Decentralized Learning Thijs Vogels, Hadrien Hendrikx, Martin Jaggi

NeurIPSW 2023 LASER: Linear Compression in Wireless Distributed Optimization Ashok Vardhan Makkuva, Marco Bondaschi, Thijs Vogels, Martin Jaggi, Hyeji Kim, Michael Gastpar

NeurIPS 2023 MultiMoDN—Multimodal, Multi-Task, Interpretable Modular Networks Vinitra Swamy, Malika Satayeva, Jibril Frej, Thierry Bossy, Thijs Vogels, Martin Jaggi, Tanja Käser, Mary-Anne Hartley

NeurIPS 2022 Beyond Spectral Gap: The Role of the Topology in Decentralized Learning Thijs Vogels, Hadrien Hendrikx, Martin Jaggi

NeurIPS 2021 RelaySum for Decentralized Deep Learning on Heterogeneous Data Thijs Vogels, Lie He, Anastasiia Koloskova, Sai Praneeth Karimireddy, Tao Lin, Sebastian U Stich, Martin Jaggi

ICML 2020 Optimizer Benchmarking Needs to Account for Hyperparameter Tuning Prabhu Teja Sivaprasad, Florian Mai, Thijs Vogels, Martin Jaggi, François Fleuret

NeurIPS 2020 Practical Low-Rank Communication Compression in Decentralized Deep Learning Thijs Vogels, Sai Praneeth Karimireddy, Martin Jaggi

NeurIPS 2019 PowerSGD: Practical Low-Rank Gradient Compression for Distributed Optimization Thijs Vogels, Sai Praneeth Karimireddy, Martin Jaggi