Kyle Matoba

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 9

Top Topics

Positive Effects

Top Venues

Trans. Mach. Learn. Res.

Publications

Arnaud Pannatier, Kyle Matoba, François Fleuret
Inference from Real-World Sparse Measurements. Trans. Mach. Learn. Res. 2024 (2024)
Kyle Matoba, Nikolaos Dimitriadis, François Fleuret
Benefits of Max Pooling in Neural Networks: Theoretical and Experimental Evidence. Trans. Mach. Learn. Res. 2023 (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)
Arnaud Pannatier, Kyle Matoba, François Fleuret
Accurate Extrinsic Prediction of Physical Systems Using Transformers. CoRR (2022)
Kyle Matoba, Nikolaos Dimitriadis, François Fleuret
The Theoretical Expressiveness of Maxpooling. CoRR (2022)
Suraj Srinivas, Kyle Matoba, Himabindu Lakkaraju, François Fleuret
Efficient Training of Low-Curvature Neural Networks. NeurIPS (2022)
Suraj Srinivas, Kyle Matoba, Himabindu Lakkaraju, François Fleuret
Flatten the Curve: Efficiently Training Low-Curvature Neural Networks. CoRR (2022)
David Lindner, Kyle Matoba, Alexander Meulemans
Challenges for Using Impact Regularizers to Avoid Negative Side Effects. CoRR (2021)
David Lindner, Kyle Matoba, Alexander Meulemans
Challenges for Using Impact Regularizers to Avoid Negative Side Effects. SafeAI@AAAI (2021)
Makoto Matsumoto, Mutsuo Saito, Kyle Matoba
A computable figure of merit for quasi-Monte Carlo point sets. Math. Comput. 83 (287) (2014)