Martin Jaggi
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
78
Venues
18
Active years
2010–2026
Best venue rank
A*
Where they publish
Papers
78 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | ACL | Apertus: Democratizing Open and Compliant LLMs for Global Language Environments. | Alejandro Hernndez-Cano, Alexander Hgele, Allen Hao Huang, Angelika Romanou, Antoni-Joan Solergibert i Llaquet, Barna Psztor, Bettina Messmer, Dhia Garbaya, Eduard Frank Durech, Ido Hakimi, Juan Garcia Giraldo, Mete Ismayilzada, Negar Foroutan, Skander Moalla, Tiancheng Chen, Vinko Sabolcec, Yixuan Even Xu, Michael Aerni, Badr AlKhamissi, Ines Altemir Marinas, Mohammad Hossein Amani, Matin Ansaripour, Ilia Badanin, Harold Benoit, Emanuela Boros, Nicholas John Browning, Fabian Bsch, Maximilian Bther, Niklas Canova, Camille Challier, Clment Charmillot, Jonathan Coles, Jan Milan Deriu, Arnout Devos, Lukas Drescher, Daniil Dzenhaliou, Maud Ehrmann, Dongyang Fan, Simin Fan, Silin Gao, Miguel Gila, Mara Grandury, Diba Hashemi, Alexander Miserlis Hoyle, Jiaming Jiang, Mark Klein, Andrei Kucharavy, Anastasiia Kucherenko, Frederike Lbeck, Roman Machacek, Theofilos Ioannis Manitaras, Andreas Marfurt, Kyle Matoba, Simon Matrenok, Henrique Mendona, Fawzi Roberto Mohamed, Syrielle Montariol, Luca Mouchel, Sven Najem-Meyer, Jingwei Ni, Gennaro Oliva, Matteo Pagliardini, Elia Palme, Andrei Panferov, Lo Paoletti, Marco Passerini, Ivan Pavlov, Auguste Poiroux, Kaustubh Ponkshe, Nathan Ranchin, Javier Rando, Mathieu Sauser, Jakhongir Saydaliev, Mukhammadali Sayfiddinov, Marian Schneider, Stefano Schuppli, Marco Scialanga, Andrei Semenov, Kumar Shridhar, Raghav Singhal, Anna Sotnikova, Alexander Sternfeld, Ayush Kumar Tarun, Paul Teiletche, Jannis Vamvas, Xiaozhe Yao, Hao Zhao, Alexander Ilic, Ana Klimovic, Andreas Krause, Caglar Gulcehre, David Rosenthal, Elliott Ash, Florian Tramr, Joost VandeVondele, Livio Veraldi, Martin Rajman, Thomas C. Schulthess, Torsten Hoefler, Antoine Bosselut, Martin Jaggi, Imanol Schlag |
| 2025 | AISTATS | Improving Stochastic Cubic Newton with Momentum. | El Mahdi Chayti, Nikita Doikov, Martin Jaggi |
| 2025 | ICLR | Effective Interplay between Sparsity and Quantization: From Theory to Practice. | Simla Burcu Harma, Ayan Chakraborty, Elizaveta Kostenok, Danila Mishin, Dongho Ha, Babak Falsafi, Martin Jaggi, Ming Liu, Yunho Oh, Suvinay Subramanian, Amir Yazdanbakhsh |
| 2025 | ICLR | Attention with Markov: A Curious Case of Single-layer Transformers. | Ashok Vardhan Makkuva, Marco Bondaschi, Adway Girish, Alliot Nagle, Martin Jaggi, Hyeji Kim, Michael Gastpar |
| 2025 | ICLR | CoTFormer: A Chain of Thought Driven Architecture with Budget-Adaptive Computation Cost at Inference. | Amirkeivan Mohtashami, Matteo Pagliardini, Martin Jaggi |
| 2025 | ICLR | Intrinsic User-Centric Interpretability through Global Mixture of Experts. | Vinitra Swamy, Syrielle Montariol, Julian Blackwell, Jibril Frej, Martin Jaggi, Tanja Kser |
| 2025 | ICML | On-Device Collaborative Language Modeling via a Mixture of Generalists and Specialists. | Dongyang Fan, Bettina Messmer, Nikita Doikov, Martin Jaggi |
| 2024 | AAAI | Ghost Noise for Regularizing Deep Neural Networks. | Atli Kosson, Dongyang Fan, Martin Jaggi |
| 2024 | ICLR | Layer-wise linear mode connectivity. | Linara Adilova, Maksym Andriushchenko, Michael Kamp, Asja Fischer, Martin Jaggi |
| 2024 | ICML | The Privacy Power of Correlated Noise in Decentralized Learning. | Youssef Allouah, Anastasia Koloskova, Aymane El Firdoussi, Martin Jaggi, Rachid Guerraoui |
| 2024 | ICML | Spectral Preconditioning for Gradient Methods on Graded Non-convex Functions. | Nikita Doikov, Sebastian U. Stich, Martin Jaggi |
| 2024 | ICML | DOGE: Domain Reweighting with Generalization Estimation. | Simin Fan, Matteo Pagliardini, Martin Jaggi |
| 2024 | ICML | On Convergence of Incremental Gradient for Non-convex Smooth Functions. | Anastasia Koloskova, Nikita Doikov, Sebastian U. Stich, Martin Jaggi |
| 2024 | ICML | Rotational Equilibrium: How Weight Decay Balances Learning Across Neural Networks. | Atli Kosson, Bettina Messmer, Martin Jaggi |
| 2024 | ICML | LASER: Linear Compression in Wireless Distributed Optimization. | Ashok Vardhan Makkuva, Marco Bondaschi, Thijs Vogels, Martin Jaggi, Hyeji Kim, Michael Gastpar |
| 2023 | ACL | SIMSUM: Document-level Text Simplification via Simultaneous Summarization. | Sofia Blinova, Xinyu Zhou, Martin Jaggi, Carsten Eickhoff, Seyed Ali Bahrainian |
| 2023 | COLT | Linearization Algorithms for Fully Composite Optimization. | Maria-Luiza Vladarean, Nikita Doikov, Martin Jaggi, Nicolas Flammarion |
| 2023 | ICLR | Agree to Disagree: Diversity through Disagreement for Better Transferability. | Matteo Pagliardini, Martin Jaggi, Franois Fleuret, Sai Praneeth Karimireddy |
| 2023 | ICML | Second-Order Optimization with Lazy Hessians. | Nikita Doikov, El Mahdi Chayti, Martin Jaggi |
| 2023 | ICML | Special Properties of Gradient Descent with Large Learning Rates. | Amirkeivan Mohtashami, Martin Jaggi, Sebastian U. Stich |
| 2022 | AAAI | Implicit Gradient Alignment in Distributed and Federated Learning. | Yatin Dandi, Luis Barba, Martin Jaggi |
| 2022 | AISTATS | Masked Training of Neural Networks with Partial Gradients. | Amirkeivan Mohtashami, Martin Jaggi, Sebastian U. Stich |
| 2022 | ICLR | Byzantine-Robust Learning on Heterogeneous Datasets via Bucketing. | Sai Praneeth Karimireddy, Lie He, Martin Jaggi |
| 2022 | NAACL | SKILL: Structured Knowledge Infusion for Large Language Models. | Fedor Moiseev, Zhe Dong, Enrique Alfonseca, Martin Jaggi |
| 2021 | ACL | Obtaining Better Static Word Embeddings Using Contextual Embedding Models. | Prakhar Gupta, Martin Jaggi |
| 2021 | ACL | Lightweight Cross-Lingual Sentence Representation Learning. | Zhuoyuan Mao, Prakhar Gupta, Chenhui Chu, Martin Jaggi, Sadao Kurohashi |
| 2021 | AISTATS | LENA: Communication-Efficient Distributed Learning with Self-Triggered Gradient Uploads. | Hossein Shokri Ghadikolaei, Sebastian U. Stich, Martin Jaggi |
| 2021 | AISTATS | A Linearly Convergent Algorithm for Decentralized Optimization: Sending Less Bits for Free! | Dmitry Kovalev, Anastasia Koloskova, Martin Jaggi, Peter Richtrik, Sebastian U. Stich |
| 2021 | AISTATS | Critical Parameters for Scalable Distributed Learning with Large Batches and Asynchronous Updates. | Sebastian U. Stich, Amirkeivan Mohtashami, Martin Jaggi |
| 2021 | EMNLP | Self-Supervised Neural Topic Modeling. | Seyed Ali Bahrainian, Martin Jaggi, Carsten Eickhoff |
| 2021 | HiPC | Faster Parallel Training of Word Embeddings. | Eliza Wszola, Martin Jaggi, Markus Pschel |
| 2021 | ICCV | Semantic Perturbations with Normalizing Flows for Improved Generalization. | Oguz Kaan Yksel, Sebastian U. Stich, Martin Jaggi, Tatjana Chavdarova |
| 2021 | ICLR | Taming GANs with Lookahead-Minmax. | Tatjana Chavdarova, Matteo Pagliardini, Sebastian U. Stich, Franois Fleuret, Martin Jaggi |
| 2021 | ICLR | Understanding the effects of data parallelism and sparsity on neural network training. | Namhoon Lee, Thalaiyasingam Ajanthan, Philip H. S. Torr, Martin Jaggi |
| 2021 | ICML | Consensus Control for Decentralized Deep Learning. | Lingjing Kong, Tao Lin, Anastasia Koloskova, Martin Jaggi, Sebastian U. Stich |
| 2021 | ICML | Quasi-global Momentum: Accelerating Decentralized Deep Learning on Heterogeneous Data. | Tao Lin, Sai Praneeth Karimireddy, Sebastian U. Stich, Martin Jaggi |
| 2021 | ICML | Exact Optimization of Conformal Predictors via Incremental and Decremental Learning. | Giovanni Cherubin, Konstantinos Chatzikokolakis, Martin Jaggi |
| 2021 | ICML | Learning from History for Byzantine Robust Optimization. | Sai Praneeth Karimireddy, Lie He, Martin Jaggi |
| 2021 | MICRO | Equinox: Training (for Free) on a Custom Inference Accelerator. | Mario Drumond, Louis Coulon, Arash Pourhabibi Zarandi, Ahmet Caner Yzgler, Babak Falsafi, Martin Jaggi |
| 2021 | Mobisys | Prediction of self-reported depression scores using person-generated health data from a virtual 1-year mental health observational study. | Mariko Makhmutova, Raghu Kainkaryam, Marta Ferreira, Jae Min, Martin Jaggi, Ieuan Clay |
| 2020 | AISTATS | Linearly Convergent Frank-Wolfe without Line-Search. | Fabian Pedregosa, Geoffrey Ngiar, Armin Askari, Martin Jaggi |
| 2020 | AISTATS | Context Mover's Distance & Barycenters: Optimal Transport of Contexts for Building Representations. | Sidak Pal Singh, Andreas Hug, Aymeric Dieuleveut, Martin Jaggi |
| 2020 | EMNLP | Masking as an Efficient Alternative to Finetuning for Pretrained Language Models. | Mengjie Zhao, Tao Lin, Fei Mi, Martin Jaggi, Hinrich Schtze |
| 2020 | ICLR | On the Relationship between Self-Attention and Convolutional Layers. | Jean-Baptiste Cordonnier, Andreas Loukas, Martin Jaggi |
| 2020 | ICLR | Decentralized Deep Learning with Arbitrary Communication Compression. | Anastasia Koloskova, Tao Lin, Sebastian U. Stich, Martin Jaggi |
| 2020 | ICLR | Dynamic Model Pruning with Feedback. | Tao Lin, Sebastian U. Stich, Luis Barba, Daniil Dmitriev, Martin Jaggi |
| 2020 | ICLR | Don't Use Large Mini-batches, Use Local SGD. | Tao Lin, Sebastian U. Stich, Kumar Kshitij Patel, Martin Jaggi |
| 2020 | ICLR | Evaluating The Search Phase of Neural Architecture Search. | Kaicheng Yu, Christian Sciuto, Martin Jaggi, Claudiu Musat, Mathieu Salzmann |
| 2020 | ICML | A Unified Theory of Decentralized SGD with Changing Topology and Local Updates. | Anastasia Koloskova, Nicolas Loizou, Sadra Boreiri, Martin Jaggi, Sebastian U. Stich |
| 2020 | ICML | Extrapolation for Large-batch Training in Deep Learning. | Tao Lin, Lingjing Kong, Sebastian U. Stich, Martin Jaggi |
| 2020 | ICML | Optimizer Benchmarking Needs to Account for Hyperparameter Tuning. | Prabhu Teja Sivaprasad, Florian Mai, Thijs Vogels, Martin Jaggi, Franois Fleuret |
| 2020 | MICCAI | Weight Erosion: An Update Aggregation Scheme for Personalized Collaborative Machine Learning. | Felix Grimberg, Mary-Anne Hartley, Martin Jaggi, Sai Praneeth Karimireddy |
| 2019 | AISTATS | Efficient Greedy Coordinate Descent for Composite Problems. | Sai Praneeth Karimireddy, Anastasia Koloskova, Sebastian U. Stich, Martin Jaggi |
| 2019 | HiPC | On Linear Learning with Manycore Processors. | Eliza Wszola, Celestine Mendler-Dnner, Martin Jaggi, Markus Pschel |
| 2019 | ICLR | Context Mover's Distance & Barycenters: Optimal transport of contexts for building representations. | Sidak Pal Singh, Andreas Hug, Aymeric Dieuleveut, Martin Jaggi |
| 2019 | ICML | Overcoming Multi-model Forgetting. | Yassine Benyahia, Kaicheng Yu, Kamil Bennani-Smires, Martin Jaggi, Anthony C. Davison, Mathieu Salzmann, Claudiu Musat |
| 2019 | ICML | Error Feedback Fixes SignSGD and other Gradient Compression Schemes. | Sai Praneeth Karimireddy, Quentin Rebjock, Sebastian U. Stich, Martin Jaggi |
| 2019 | ICML | Decentralized Stochastic Optimization and Gossip Algorithms with Compressed Communication. | Anastasia Koloskova, Sebastian U. Stich, Martin Jaggi |
| 2019 | Interspeech | Open-Vocabulary Keyword Spotting with Audio and Text Embeddings. | Niccol Sacchi, Alexandre Nanchen, Martin Jaggi, Milos Cernak |
| 2019 | NAACL | Better Word Embeddings by Disentangling Contextual n-Gram Information. | Prakhar Gupta, Matteo Pagliardini, Martin Jaggi |
| 2019 | WSDM | Crosslingual Document Embedding as Reduced-Rank Ridge Regression. | Martin Josifoski, Ivan S. Paskov, Hristo S. Paskov, Martin Jaggi, Robert West |
| 2018 | AISTATS | Adaptive balancing of gradient and update computation times using global geometry and approximate subproblems. | Sai Praneeth Reddy Karimireddy, Sebastian U. Stich, Martin Jaggi |
| 2018 | CoNLL | Simple Unsupervised Keyphrase Extraction using Sentence Embeddings. | Kamil Bennani-Smires, Claudiu Musat, Andreea Hossmann, Michael Baeriswyl, Martin Jaggi |
| 2018 | ICML | A Distributed Second-Order Algorithm You Can Trust. | Celestine Dnner, Aurlien Lucchi, Matilde Gargiani, An Bian, Thomas Hofmann, Martin Jaggi |
| 2018 | ICML | On Matching Pursuit and Coordinate Descent. | Francesco Locatello, Anant Raj, Sai Praneeth Karimireddy, Gunnar Rtsch, Bernhard Schlkopf, Sebastian U. Stich, Martin Jaggi |
| 2018 | NAACL | Unsupervised Learning of Sentence Embeddings Using Compositional n-Gram Features. | Matteo Pagliardini, Prakhar Gupta, Martin Jaggi |
| 2017 | ACL | Generating Steganographic Text with LSTMs. | Tina Fang, Martin Jaggi, Katerina J. Argyraki |
| 2017 | AISTATS | A Unified Optimization View on Generalized Matching Pursuit and Frank-Wolfe. | Francesco Locatello, Rajiv Khanna, Michael Tschannen, Martin Jaggi |
| 2017 | AISTATS | Faster Coordinate Descent via Adaptive Importance Sampling. | Dmytro Perekrestenko, Volkan Cevher, Martin Jaggi |
| 2017 | ICML | Approximate Steepest Coordinate Descent. | Sebastian U. Stich, Anant Raj, Martin Jaggi |
| 2017 | WWW | Leveraging Large Amounts of Weakly Supervised Data for Multi-Language Sentiment Classification. | Jan Deriu, Aurlien Lucchi, Valeria De Luca, Aliaksei Severyn, Simon Mller, Mark Cieliebak, Thomas Hofmann, Martin Jaggi |
| 2016 | ICML | Primal-Dual Rates and Certificates. | Celestine Dnner, Simone Forte, Martin Takc, Martin Jaggi |
| 2015 | ICML | Adding vs. Averaging in Distributed Primal-Dual Optimization. | Chenxin Ma, Virginia Smith, Martin Jaggi, Michael I. Jordan, Peter Richtrik, Martin Takc |
| 2013 | ICML | Revisiting Frank-Wolfe: Projection-Free Sparse Convex Optimization. | Martin Jaggi |
| 2013 | ICML | Block-Coordinate Frank-Wolfe Optimization for Structural SVMs. | Simon Lacoste-Julien, Martin Jaggi, Mark Schmidt, Patrick Pletscher |
| 2012 | ESA | Optimizing over the Growing Spectrahedron. | Joachim Giesen, Martin Jaggi, Sren Laue |
| 2010 | ESA | Approximating Parameterized Convex Optimization Problems. | Joachim Giesen, Martin Jaggi, Sren Laue |
| 2010 | ICML | A Simple Algorithm for Nuclear Norm Regularized Problems. | Martin Jaggi, Marek Sulovsk |