Martin Jaggi

ORCID

Publication Activity (10 Years)

Years Active: 2009-2024
Publications (10 Years): 214

Top Venues

Publications

Simin Fan, Razvan Pascanu, Martin Jaggi
Deep Grokking: Would Deep Neural Networks Generalize Better? CoRR (2024)
Saleh Ashkboos, Amirkeivan Mohtashami, Maximilian L. Croci, Bo Li, Martin Jaggi, Dan Alistarh, Torsten Hoefler, James Hensman
QuaRot: Outlier-Free 4-Bit Inference in Rotated LLMs. CoRR (2024)
Ashok Vardhan Makkuva, Marco Bondaschi, Adway Girish, Alliot Nagle, Martin Jaggi, Hyeji Kim, Michael Gastpar
Attention with Markov: A Framework for Principled Analysis of Transformers via Markov Chains. CoRR (2024)
Alexander Hägele, Elie Bakouch, Atli Kosson, Loubna Ben Allal, Leandro von Werra, Martin Jaggi
Scaling Laws and Compute-Optimal Training Beyond Fixed Training Durations. CoRR (2024)
Matteo Pagliardini, Amirkeivan Mohtashami, François Fleuret, Martin Jaggi
DenseFormer: Enhancing Information Flow in Transformers via Depth Weighted Averaging. CoRR (2024)
Nicolas Wagner, Dongyang Fan, Martin Jaggi
Personalized Collaborative Fine-Tuning for On-Device Large Language Models. CoRR (2024)
Dongyang Fan, Bettina Messmer, Martin Jaggi
Towards an empirical understanding of MoE design choices. CoRR (2024)
Youssef Allouah, Anastasia Koloskova, Aymane El Firdoussi, Martin Jaggi, Rachid Guerraoui
The Privacy Power of Correlated Noise in Decentralized Learning. CoRR (2024)
Linara Adilova, Maksym Andriushchenko, Michael Kamp, Asja Fischer, Martin Jaggi
Layer-wise linear mode connectivity. ICLR (2024)
Simla Burcu Harma, Ayan Chakraborty, Elizaveta Kostenok, Danila Mishin, Dongho Ha, Babak Falsafi, Martin Jaggi, Ming Liu, Yunho Oh, Suvinay Subramanian, Amir Yazdanbakhsh
Effective Interplay between Sparsity and Quantization: From Theory to Practice. CoRR (2024)
Vinitra Swamy, Julian Blackwell, Jibril Frej, Martin Jaggi, Tanja Käser
InterpretCC: Conditional Computation for Inherently Interpretable Neural Networks. CoRR (2024)
Atli Kosson, Dongyang Fan, Martin Jaggi
Ghost Noise for Regularizing Deep Neural Networks. AAAI (2024)
Julien Heitmann, Alban Glangetas, Jonathan Doenz, Juliane Dervaux, Deeksha M. Shama, Daniel Hinjos Garcia, Mohamed Rida Benissa, Aymeric Cantais, Alexandre Perez, Daniel Müller, Tatjana Chavdarova, Isabelle Ruchonnet-Metrailler, Johan N. Siebert, Laurence Lacroix, Martin Jaggi, Alain Gervaix, Mary-Anne Hartley, Florence Hugon, Derrick Fassbind, Makura Barro, Georges Bediang, N. E. L. Hafidi, M. Bouskraoui, Idrissa Ba
DeepBreath - automated detection of respiratory pathology from lung auscultation in 572 pediatric outpatients across 5 countries. npj Digit. Medicine 6 (2023)
Matteo Pagliardini, Martin Jaggi, François Fleuret, Sai Praneeth Karimireddy
Agree to Disagree: Diversity through Disagreement for Better Transferability. ICLR (2023)
Maria-Luiza Vladarean, Nikita Doikov, Martin Jaggi, Nicolas Flammarion
Linearization Algorithms for Fully Composite Optimization. COLT (2023)
Thijs Vogels, Hadrien Hendrikx, Martin Jaggi
Beyond spectral gap (extended): The role of the topology in decentralized learning. CoRR (2023)
El Mahdi Chayti, Nikita Doikov, Martin Jaggi
Unified Convergence Theory of Stochastic and Variance-Reduced Cubic Newton Methods. CoRR (2023)
Sofia Blinova, Xinyu Zhou, Martin Jaggi, Carsten Eickhoff, Seyed Ali Bahrainian
SIMSUM: Document-level Text Simplification via Simultaneous Summarization. ACL (1) (2023)
Amirkeivan Mohtashami, Matteo Pagliardini, Martin Jaggi
CoTFormer: More Tokens With Attention Make Up For Less Depth. CoRR (2023)
Maria-Luiza Vladarean, Nikita Doikov, Martin Jaggi, Nicolas Flammarion
Linearization Algorithms for Fully Composite Optimization. CoRR (2023)
Nikita Doikov, El Mahdi Chayti, Martin Jaggi
Second-Order Optimization with Lazy Hessians. ICML (2023)
Mariel A. Werner, Lie He, Sai Praneeth Karimireddy, Michael I. Jordan, Martin Jaggi
Provably Personalized and Robust Federated Learning. CoRR (2023)
Linara Adilova, Asja Fischer, Martin Jaggi
Layerwise Linear Mode Connectivity. CoRR (2023)
Anastasia Koloskova, Nikita Doikov, Sebastian U. Stich, Martin Jaggi
Shuffle SGD is Always Better than SGD: Improved Analysis of SGD with Arbitrary Data Orders. CoRR (2023)
Atli Kosson, Bettina Messmer, Martin Jaggi
Rotational Optimizers: Simple & Robust DNN Training. CoRR (2023)
Simin Fan, Martin Jaggi
Irreducible Curriculum for Language Model Pretraining. CoRR (2023)
Seyed Ali Bahrainian, Martin Jaggi, Carsten Eickhoff
Controllable Topic-Focused Abstractive Summarization. CoRR (2023)
Amirkeivan Mohtashami, Martin Jaggi
Landmark Attention: Random-Access Infinite Context Length for Transformers. CoRR (2023)
Atli Kosson, Martin Jaggi
Hardware-Efficient Transformer Training via Piecewise Affine Operations. CoRR (2023)
Vinitra Swamy, Malika Satayeva, Jibril Frej, Thierry Bossy, Thijs Vogels, Martin Jaggi, Tanja Käser, Mary-Anne Hartley
MultiMoDN - Multimodal, Multi-Task, Interpretable Modular Networks. NeurIPS (2023)
Matteo Pagliardini, Daniele Paliotta, Martin Jaggi, François Fleuret
Faster Causal Attention Over Large Sequences Through Sparse Flash Attention. CoRR (2023)
Mariel A. Werner, Lie He, Michael I. Jordan, Martin Jaggi, Sai Praneeth Karimireddy
Provably Personalized and Robust Federated Learning. Trans. Mach. Learn. Res. 2023 (2023)
Ashok Vardhan Makkuva, Marco Bondaschi, Thijs Vogels, Martin Jaggi, Hyeji Kim, Michael C. Gastpar
LASER: Linear Compression in Wireless Distributed Optimization. CoRR (2023)
Dongyang Fan, Celestine Mendler-Dünner, Martin Jaggi
Collaborative Learning via Prediction Consensus. NeurIPS (2023)
Atli Kosson, Dongyang Fan, Martin Jaggi
Ghost Noise for Regularizing Deep Neural Networks. CoRR (2023)
Zeming Chen, Alejandro Hernández-Cano, Angelika Romanou, Antoine Bonnet, Kyle Matoba, Francesco Salvi, Matteo Pagliardini, Simin Fan, Andreas Köpf, Amirkeivan Mohtashami, Alexandre Sallinen, Alireza Sakhaeirad, Vinitra Swamy, Igor Krawczuk, Deniz Bayazit, Axel Marmet, Syrielle Montariol, Mary-Anne Hartley, Martin Jaggi, Antoine Bosselut
MEDITRON-70B: Scaling Medical Pretraining for Large Language Models. CoRR (2023)
Amirkeivan Mohtashami, Martin Jaggi, Sebastian U. Stich
Special Properties of Gradient Descent with Large Learning Rates. ICML (2023)
Vinitra Swamy, Malika Satayeva, Jibril Frej, Thierry Bossy, Thijs Vogels, Martin Jaggi, Tanja Käser, Mary-Anne Hartley
MultiModN- Multimodal, Multi-Task, Interpretable Modular Networks. CoRR (2023)
Atli Kosson, Martin Jaggi
Multiplication-Free Transformer Training via Piecewise Affine Operations. NeurIPS (2023)
Amirkeivan Mohtashami, Martin Jaggi
Random-Access Infinite Context Length for Transformers. NeurIPS (2023)
Simin Fan, Matteo Pagliardini, Martin Jaggi
DoGE: Domain Reweighting with Generalization Estimation. CoRR (2023)
Dongyang Fan, Celestine Mendler-Dünner, Martin Jaggi
Collaborative Learning via Prediction Consensus. CoRR (2023)
Matteo Pagliardini, Daniele Paliotta, Martin Jaggi, François Fleuret
Fast Attention Over Long Sequences With Dynamic Sparse Flash Attention. NeurIPS (2023)
Frédéric Berdoz, Abhishek Singh, Martin Jaggi, Ramesh Raskar
Scalable Collaborative Learning via Representation Sharing. CoRR (2022)
Matteo Pagliardini, Martin Jaggi, François Fleuret, Sai Praneeth Karimireddy
Agree to Disagree: Diversity through Disagreement for Better Transferability. CoRR (2022)
Amirkeivan Mohtashami, Martin Jaggi, Sebastian U. Stich
On Avoiding Local Minima Using Gradient Descent With Large Learning Rates. CoRR (2022)
Matteo Pagliardini, Gilberto Manunza, Martin Jaggi, Michael I. Jordan, Tatjana Chavdarova
Improving Generalization via Uncertainty Driven Perturbations. CoRR (2022)
Yatin Dandi, Luis Barba, Martin Jaggi
Implicit Gradient Alignment in Distributed and Federated Learning. AAAI (2022)
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 S. Silva R., Maria Telenczuk, Shadi Albarqouni, Salman Avestimehr, Aurélien Bellet, Aymeric Dieuleveut, Martin Jaggi, Sai Praneeth Karimireddy, Marco Lorenzi, Giovanni Neglia, Marc Tommasi, Mathieu Andreux
FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings. CoRR (2022)
Nikita Doikov, El Mahdi Chayti, Martin Jaggi
Second-order optimization with lazy Hessians. CoRR (2022)
Anastasia Koloskova, Sebastian U. Stich, Martin Jaggi
Sharper Convergence Guarantees for Asynchronous SGD for Distributed and Federated Learning. NeurIPS (2022)
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 Telenczuk, Shadi Albarqouni, Salman Avestimehr, Aurélien Bellet, Aymeric Dieuleveut, Martin Jaggi, Sai Praneeth Karimireddy, Marco Lorenzi, Giovanni Neglia, Marc Tommasi, Mathieu Andreux
FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings. NeurIPS (2022)
Yatin Dandi, Anastasia Koloskova, Martin Jaggi, Sebastian U. Stich
Data-heterogeneity-aware Mixing for Decentralized Learning. CoRR (2022)
Thijs Vogels, Hadrien Hendrikx, Martin Jaggi
Beyond spectral gap: The role of the topology in decentralized learning. CoRR (2022)
Fedor Moiseev, Zhe Dong, Enrique Alfonseca, Martin Jaggi
SKILL: Structured Knowledge Infusion for Large Language Models. CoRR (2022)
Fedor Moiseev, Zhe Dong, Enrique Alfonseca, Martin Jaggi
SKILL: Structured Knowledge Infusion for Large Language Models. NAACL-HLT (2022)
Cécile Trottet, Thijs Vogels, Martin Jaggi, Mary-Anne Hartley
Modular Clinical Decision Support Networks (MoDN) - Updatable, Interpretable, and Portable Predictions for Evolving Clinical Environments. CoRR (2022)
Sai Praneeth Karimireddy, Lie He, Martin Jaggi
Byzantine-Robust Learning on Heterogeneous Datasets via Bucketing. ICLR (2022)
Anastasia Koloskova, Sebastian U. Stich, Martin Jaggi
Sharper Convergence Guarantees for Asynchronous SGD for Distributed and Federated Learning. CoRR (2022)
Lie He, Sai Praneeth Karimireddy, Martin Jaggi
Byzantine-Robust Decentralized Learning via Self-Centered Clipping. CoRR (2022)
Simla Burcu Harma, Canberk Sönmez, Babak Falsafi, Martin Jaggi, Yunho Oh
Accuracy Boosters: Epoch-Driven Mixed-Mantissa Block Floating-Point for DNN Training. CoRR (2022)
Amirkeivan Mohtashami, Martin Jaggi, Sebastian U. Stich
Masked Training of Neural Networks with Partial Gradients. AISTATS (2022)
Amirkeivan Mohtashami, Sebastian U. Stich, Martin Jaggi
Characterizing & Finding Good Data Orderings for Fast Convergence of Sequential Gradient Methods. CoRR (2022)
Thijs Vogels, Hadrien Hendrikx, Martin Jaggi
Beyond spectral gap: the role of the topology in decentralized learning. NeurIPS (2022)
Oguz Kaan Yüksel, Sebastian U. Stich, Martin Jaggi, Tatjana Chavdarova
Semantic Perturbations with Normalizing Flows for Improved Generalization. ICCV (2021)
Prakhar Gupta, Martin Jaggi
Obtaining Better Static Word Embeddings Using Contextual Embedding Models. CoRR (2021)
Eliza Wszola, Martin Jaggi, Markus Püschel
Faster Parallel Training of Word Embeddings. HiPC (2021)
Jianyu Wang, Zachary Charles, Zheng Xu, Gauri Joshi, H. Brendan McMahan, Blaise Agüera y Arcas, Maruan Al-Shedivat, Galen Andrew, Salman Avestimehr, Katharine Daly, Deepesh Data, Suhas N. 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 Konecný, Sanmi Koyejo, Tian Li, Luyang Liu, Mehryar Mohri, Hang Qi, Sashank J. Reddi, Peter Richtárik, Karan Singhal, Virginia Smith, Mahdi Soltanolkotabi, Weikang Song, Ananda Theertha Suresh, Sebastian U. Stich, Ameet Talwalkar, Hongyi Wang, Blake E. Woodworth, Shanshan Wu, Felix X. Yu, Honglin Yuan, Manzil Zaheer, Mi Zhang, Tong Zhang, Chunxiang Zheng, Chen Zhu, Wennan Zhu
A Field Guide to Federated Optimization. CoRR (2021)
Zhuoyuan Mao, Prakhar Gupta, Chenhui Chu, Martin Jaggi, Sadao Kurohashi
Lightweight Cross-Lingual Sentence Representation Learning. CoRR (2021)
Dmitry Kovalev, Anastasia Koloskova, Martin Jaggi, Peter Richtárik, Sebastian U. Stich
A Linearly Convergent Algorithm for Decentralized Optimization: Sending Less Bits for Free! AISTATS (2021)
El Mahdi Chayti, Sai Praneeth Karimireddy, Sebastian U. Stich, Nicolas Flammarion, Martin Jaggi
Linear Speedup in Personalized Collaborative Learning. CoRR (2021)
Sai Praneeth Karimireddy, Lie He, Martin Jaggi
Learning from History for Byzantine Robust Optimization. ICML (2021)
Hossein Shokri Ghadikolaei, Sebastian U. Stich, Martin Jaggi
LENA: Communication-Efficient Distributed Learning with Self-Triggered Gradient Uploads. AISTATS (2021)
Martin Beaussart, Felix Grimberg, Mary-Anne Hartley, Martin Jaggi
WAFFLE: Weighted Averaging for Personalized Federated Learning. CoRR (2021)
Mariko Makhmutova, Raghu Kainkaryam, Marta Ferreira, Jae Min, Martin Jaggi, Ieuan Clay
Prediction of self-reported depression scores using person-generated health data from a virtual 1-year mental health observational study. DigiBiom@MobiSys (2021)
Valerian Rey, Pedro Miguel Sánchez Sánchez, Alberto Huertas Celdrán, Gérôme Bovet, Martin Jaggi
Federated Learning for Malware Detection in IoT Devices. CoRR (2021)
Chenxin Ma, Martin Jaggi, Frank E. Curtis, Nathan Srebro, Martin Takác
An accelerated communication-efficient primal-dual optimization framework for structured machine learning. Optim. Methods Softw. 36 (1) (2021)
Felix Grimberg, Mary-Anne Hartley, Sai Praneeth Karimireddy, Martin Jaggi
Optimal Model Averaging: Towards Personalized Collaborative Learning. CoRR (2021)
Oguz Kaan Yüksel, Sebastian U. Stich, Martin Jaggi, Tatjana Chavdarova
Semantic Perturbations with Normalizing Flows for Improved Generalization. CoRR (2021)
Tao Lin, Sai Praneeth Karimireddy, Sebastian U. Stich, Martin Jaggi
Quasi-global Momentum: Accelerating Decentralized Deep Learning on Heterogeneous Data. ICML (2021)
Prakhar Gupta, Martin Jaggi
Obtaining Better Static Word Embeddings Using Contextual Embedding Models. ACL/IJCNLP (1) (2021)
Sebastian U. Stich, Amirkeivan Mohtashami, Martin Jaggi
Critical Parameters for Scalable Distributed Learning with Large Batches and Asynchronous Updates. CoRR (2021)
Thijs Vogels, Lie He, Anastasia Koloskova, Tao Lin, Sai Praneeth Karimireddy, Sebastian U. Stich, Martin Jaggi
RelaySum for Decentralized Deep Learning on Heterogeneous Data. CoRR (2021)
Zhuoyuan Mao, Prakhar Gupta, Chenhui Chu, Martin Jaggi, Sadao Kurohashi
Lightweight Cross-Lingual Sentence Representation Learning. ACL/IJCNLP (1) (2021)
Vinitra Swamy, Angelika Romanou, Martin Jaggi
Interpreting Language Models Through Knowledge Graph Extraction. CoRR (2021)
Mario Drumond, Louis Coulon, Arash Pourhabibi Zarandi, Ahmet Caner Yüzügüler, Babak Falsafi, Martin Jaggi
Equinox: Training (for Free) on a Custom Inference Accelerator. MICRO (2021)
Amirkeivan Mohtashami, Martin Jaggi, Sebastian U. Stich
Simultaneous Training of Partially Masked Neural Networks. CoRR (2021)
Giovanni Cherubin, Konstantinos Chatzikokolakis, Martin Jaggi
Exact Optimization of Conformal Predictors via Incremental and Decremental Learning. ICML (2021)
Yatin Dandi, Luis Barba, Martin Jaggi
Implicit Gradient Alignment in Distributed and Federated Learning. CoRR (2021)
Giovanni Cherubin, Konstantinos Chatzikokolakis, Martin Jaggi
Exact Optimization of Conformal Predictors via Incremental and Decremental Learning. CoRR (2021)
Thijs Vogels, Lie He, Anastasia Koloskova, Sai Praneeth Karimireddy, Tao Lin, Sebastian U. Stich, Martin Jaggi
RelaySum for Decentralized Deep Learning on Heterogeneous Data. NeurIPS (2021)
Lingjing Kong, Tao Lin, Anastasia Koloskova, Martin Jaggi, Sebastian U. Stich
Consensus Control for Decentralized Deep Learning. CoRR (2021)
Lingjing Kong, Tao Lin, Anastasia Koloskova, Martin Jaggi, Sebastian U. Stich
Consensus Control for Decentralized Deep Learning. ICML (2021)
Namhoon Lee, Thalaiyasingam Ajanthan, Philip H. S. Torr, Martin Jaggi
Understanding the effects of data parallelism and sparsity on neural network training. ICLR (2021)
Sebastian U. Stich, Amirkeivan Mohtashami, Martin Jaggi
Critical Parameters for Scalable Distributed Learning with Large Batches and Asynchronous Updates. AISTATS (2021)
Seyed Ali Bahrainian, Martin Jaggi, Carsten Eickhoff
Self-Supervised Neural Topic Modeling. EMNLP (Findings) (2021)
Tatjana Chavdarova, Matteo Pagliardini, Sebastian U. Stich, François Fleuret, Martin Jaggi
Taming GANs with Lookahead-Minmax. ICLR (2021)
Tao Lin, Sai Praneeth Karimireddy, Sebastian U. Stich, Martin Jaggi
Quasi-Global Momentum: Accelerating Decentralized Deep Learning on Heterogeneous Data. CoRR (2021)
Sebastian Bischoff, Stephan Günnemann, Martin Jaggi, Sebastian U. Stich
On Second-order Optimization Methods for Federated Learning. CoRR (2021)
Sai Praneeth Karimireddy, Martin Jaggi, Satyen Kale, Mehryar Mohri, Sashank J. Reddi, Sebastian U. Stich, Ananda Theertha Suresh
Breaking the centralized barrier for cross-device federated learning. NeurIPS (2021)

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Publication Activity (10 Years)

Top Topics

Top Venues

Martin Jaggi