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2020 – today
- 2024
[c8]Tatjana Chavdarova
, Tong Yang, Matteo Pagliardini, Michael I. Jordan:
A Primal-Dual Approach to Solving Variational Inequalities with General Constraints. ICLR 2024- [c7]Simin Fan, Matteo Pagliardini, Martin Jaggi:
DOGE: Domain Reweighting with Generalization Estimation. ICML 2024 - [i13]Matteo Pagliardini, Amirkeivan Mohtashami, François Fleuret, Martin Jaggi:
DenseFormer: Enhancing Information Flow in Transformers via Depth Weighted Averaging. CoRR abs/2402.02622 (2024) - [i12]Matteo Pagliardini, Pierre Ablin, David Grangier:
The AdEMAMix Optimizer: Better, Faster, Older. CoRR abs/2409.03137 (2024) - 2023
- [c6]Matteo Pagliardini, Martin Jaggi, François Fleuret, Sai Praneeth Karimireddy:
Agree to Disagree: Diversity through Disagreement for Better Transferability. ICLR 2023 - [c5]Matteo Pagliardini, Daniele Paliotta, Martin Jaggi, François Fleuret:
Fast Attention Over Long Sequences With Dynamic Sparse Flash Attention. NeurIPS 2023 - [i11]Matteo Pagliardini, Daniele Paliotta, Martin Jaggi, François Fleuret:
Faster Causal Attention Over Large Sequences Through Sparse Flash Attention. CoRR abs/2306.01160 (2023) - [i10]Amirkeivan Mohtashami, Matteo Pagliardini, Martin Jaggi:
CoTFormer: More Tokens With Attention Make Up For Less Depth. CoRR abs/2310.10845 (2023) - [i9]Simin Fan, Matteo Pagliardini, Martin Jaggi:
DoGE: Domain Reweighting with Generalization Estimation. CoRR abs/2310.15393 (2023) - [i8]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 abs/2311.16079 (2023) - 2022
- [i7]Matteo Pagliardini, Martin Jaggi, François Fleuret, Sai Praneeth Karimireddy:
Agree to Disagree: Diversity through Disagreement for Better Transferability. CoRR abs/2202.04414 (2022) - [i6]Matteo Pagliardini, Gilberto Manunza, Martin Jaggi, Michael I. Jordan, Tatjana Chavdarova:
Improving Generalization via Uncertainty Driven Perturbations. CoRR abs/2202.05737 (2022) - [i5]Tatjana Chavdarova, Matteo Pagliardini, Tong Yang, Michael I. Jordan:
Revisiting the ACVI Method for Constrained Variational Inequalities. CoRR abs/2210.15659 (2022) - 2021
- [c4]Tatjana Chavdarova, Matteo Pagliardini, Sebastian U. Stich, François Fleuret, Martin Jaggi:
Taming GANs with Lookahead-Minmax. ICLR 2021 - [i4]Yehao Liu, Matteo Pagliardini, Tatjana Chavdarova, Sebastian U. Stich:
The Peril of Popular Deep Learning Uncertainty Estimation Methods. CoRR abs/2112.05000 (2021) - 2020
- [i3]Tatjana Chavdarova, Matteo Pagliardini, Martin Jaggi, François Fleuret:
Taming GANs with Lookahead. CoRR abs/2006.14567 (2020)
2010 – 2019
- 2019
- [c3]Prakhar Gupta, Matteo Pagliardini, Martin Jaggi:
Better Word Embeddings by Disentangling Contextual n-Gram Information. NAACL-HLT (1) 2019: 933-939 - [i2]Prakhar Gupta, Matteo Pagliardini, Martin Jaggi:
Better Word Embeddings by Disentangling Contextual n-Gram Information. CoRR abs/1904.05033 (2019) - 2018
- [c2]Matteo Pagliardini, Prakhar Gupta, Martin Jaggi:
Unsupervised Learning of Sentence Embeddings Using Compositional n-Gram Features. NAACL-HLT 2018: 528-540 - 2017
- [i1]Matteo Pagliardini, Prakhar Gupta, Martin Jaggi:
Unsupervised Learning of Sentence Embeddings using Compositional n-Gram Features. CoRR abs/1703.02507 (2017) - 2013
- [c1]Matteo Pagliardini, Yasuhiro Akagi, Marcos Slomp, Ryo Furukawa, Ryusuke Sagawa, Hiroshi Kawasaki:
Exemplar-Based Hole-Filling Technique for Multiple Dynamic Objects. PSIVT 2013: 242-253
Coauthor Index
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