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2020 – today
- 2024
[c1]Mubashara Akhtar
, Omar Benjelloun, Costanza Conforti, Pieter Gijsbers, Joan Giner-Miguelez, Nitisha Jain, Michael Kuchnik, Quentin Lhoest, Pierre Marcenac, Manil Maskey, Peter Mattson, Luis Oala, Pierre Ruyssen, Rajat Shinde, Elena Simperl, Goeffry Thomas, Slava Tykhonov, Joaquin Vanschoren, Jos van der Velde, Steffen Vogler, Carole-Jean Wu:
Croissant: A Metadata Format for ML-Ready Datasets. DEEM@SIGMOD 2024: 1-6- [i4]Mubashara Akhtar, Omar Benjelloun, Costanza Conforti, Joan Giner-Miguelez, Nitisha Jain, Michael Kuchnik, Quentin Lhoest, Pierre Marcenac, Manil Maskey, Peter Mattson, Luis Oala, Pierre Ruyssen, Rajat Shinde, Elena Simperl, Goeffry Thomas, Slava Tykhonov, Joaquin Vanschoren, Steffen Vogler, Carole-Jean Wu:
Croissant: A Metadata Format for ML-Ready Datasets. CoRR abs/2403.19546 (2024) - 2023
- [j2]Calypso Herrera, Florian Krach, Anastasis Kratsios, Pierre Ruyssen, Josef Teichmann:
Denise: Deep Robust Principal Component Analysis for Positive Semidefinite Matrices. Trans. Mach. Learn. Res. 2023 (2023) - [j1]Michel Baes, Calypso Herrera, Ariel Neufeld, Pierre Ruyssen:
Low-Rank Plus Sparse Decomposition of Covariance Matrices Using Neural Network Parametrization. IEEE Trans. Neural Networks Learn. Syst. 34(1): 171-185 (2023) - 2021
- [i3]Calypso Herrera, Florian Krach, Pierre Ruyssen, Josef Teichmann:
Optimal Stopping via Randomized Neural Networks. CoRR abs/2104.13669 (2021)
2010 – 2019
- 2019
- [i2]Michel Baes, Calypso Herrera, Ariel Neufeld, Pierre Ruyssen:
Low-Rank plus Sparse Decomposition of Covariance Matrices using Neural Network Parametrization. CoRR abs/1908.00461 (2019) - [i1]Xiaohua Zhai, Joan Puigcerver, Alexander Kolesnikov, Pierre Ruyssen, Carlos Riquelme, Mario Lucic, Josip Djolonga, André Susano Pinto, Maxim Neumann, Alexey Dosovitskiy, Lucas Beyer, Olivier Bachem, Michael Tschannen, Marcin Michalski, Olivier Bousquet, Sylvain Gelly, Neil Houlsby:
The Visual Task Adaptation Benchmark. CoRR abs/1910.04867 (2019)
Coauthor Index
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