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Omar Rivasplata
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Tighter risk certificates for neural networks
M Pérez-Ortiz, O Rivasplata, J Shawe-Taylor, C Szepesvári
Journal of Machine Learning Research 22 (227), 1-40, 2021
1152021
Logarithmic pruning is all you need
L Orseau, M Hutter, O Rivasplata
Advances in Neural Information Processing Systems 33, 2925-2934, 2020
982020
Subgaussian random variables: An expository note
O Rivasplata
Internet publication, PDF 5, 2012
96*2012
PAC-Bayes analysis beyond the usual bounds
O Rivasplata, I Kuzborskij, C Szepesvári, J Shawe-Taylor
Advances in Neural Information Processing Systems 33, 16833-16845, 2020
842020
PAC-Bayes bounds for stable algorithms with instance-dependent priors
O Rivasplata, E Parrado-Hernández, JS Shawe-Taylor, S Sun, ...
Advances in Neural Information Processing Systems 31, 2018
572018
PAC-Bayes with backprop
O Rivasplata, VM Tankasali, C Szepesvari
arXiv preprint arXiv:1908.07380, 2019
532019
Smallest singular value of sparse random matrices
A Litvak, O Rivasplata
Studia Math 212, 195-218, 2012
272012
Learning PAC-Bayes priors for probabilistic neural networks
M Perez-Ortiz, O Rivasplata, B Guedj, M Gleeson, J Zhang, ...
arXiv preprint arXiv:2109.10304, 2021
192021
Progress in self-certified neural networks
M Perez-Ortiz, O Rivasplata, E Parrado-Hernandez, B Guedj, ...
arXiv preprint arXiv:2111.07737, 2021
152021
On the role of optimization in double descent: A least squares study
I Kuzborskij, C Szepesvári, O Rivasplata, A Rannen-Triki, R Pascanu
Advances in Neural Information Processing Systems 34, 29567-29577, 2021
122021
Statistical learning theory: A hitchhiker’s guide
J Shawe-Taylor, O Rivasplata
NeurIPS 2018, 2018
42018
Towards Better Visual Explanations for Deep Image Classifiers
A Grabska-Barwinska, A Rannen-Triki, O Rivasplata, A György
NeurIPS 2020 Workshop eXplainable AI approaches for debugging and diagnosis., 2021
32021
Towards self-certified learning: Probabilistic neural networks trained by PAC-Bayes with backprop
M Pérez-Ortiz, O Rivasplata, J Shawe-Taylor, C Szepesvári
NeurIPS 2020 Workshop - Beyond Backpropagation, 2020
22020
A Note on the Convergence of Denoising Diffusion Probabilistic Models
SD Mbacke, O Rivasplata
arXiv preprint arXiv:2312.05989, 2023
12023
Semi-counterfactual risk minimization via neural networks
G Aminian, R Vega, O Rivasplata, L Toni, M Rodrigues
arXiv preprint arXiv:2209.07148, 2022
12022
PAC-Bayesian Computation
O Rivasplata
University College London, 2022
12022
Reversibility for diffusions via quasi-invarience
O Rivasplata, J Rychtář, B Schmuland
Acta Universitatis Carolinae. Mathematica et Physica 48 (1), 3-10, 2007
12007
A note on generalization bounds for losses with finite moments
B Rodríguez-Gálvez, O Rivasplata, R Thobaben, M Skoglund
arXiv preprint arXiv:2403.16681, 2024
2024
A note on a confidence bound of Kuzborskij and Szepesvári
O Rivasplata
arXiv preprint arXiv:2101.04671, 2021
2021
Image recovery via compressive sensing with sparsifying DCT and DFT transforms
M Halma, M Sacchi, O Rivasplata
2014
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