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Ilja Kuzborskij
Ilja Kuzborskij
DeepMind
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Title
Cited by
Cited by
Year
Characterization of a benchmark database for myoelectric movement classification
M Atzori, A Gijsberts, I Kuzborskij, S Elsig, AGM Hager, O Deriaz, ...
IEEE transactions on neural systems and rehabilitation engineering 23 (1), 73-83, 2014
2052014
From n to n+ 1: Multiclass transfer incremental learning
I Kuzborskij, F Orabona, B Caputo
Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2013
1552013
Stability and hypothesis transfer learning
I Kuzborskij, F Orabona
International Conference on Machine Learning, 942-950, 2013
1482013
On the challenge of classifying 52 hand movements from surface electromyography
I Kuzborskij, A Gijsberts, B Caputo
2012 annual international conference of the IEEE engineering in medicine and …, 2012
1272012
Data-Dependent Stability of Stochastic Gradient Descent
I Kuzborskij, CH Lampert
International Conference on Machine Learning, 2018
1002018
Fast Rates by Transferring from Auxiliary Hypotheses
I Kuzborskij, F Orabona
Machine Learning, 2016
522016
PAC-Bayes analysis beyond the usual bounds
O Rivasplata, I Kuzborskij, C Szepesvári, J Shawe-Taylor
Advances in Neural Information Processing Systems (NeurIPS) 33, 2020
382020
When Naive Bayes Nearest Neighbours Meet Convolutional Neural Networks
I Kuzborskij, FM Carlucci, B Caputo
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2016
292016
Transfer Learning through Greedy Subset Selection
I Kuzborskij, B Caputo, F Orabona
18th International Conference on Image Analysis and Processing — ICIAP 2015, 2015
252015
Scalable greedy algorithms for transfer learning
I Kuzborskij, F Orabona, B Caputo
Computer Vision and Image Understanding 156, 174-185, 2017
192017
Confident off-policy evaluation and selection through self-normalized importance weighting
I Kuzborskij, C Vernade, A Gyorgy, C Szepesvári
International Conference on Artificial Intelligence and Statistics (AISTATS …, 2021
182021
Efficient linear bandits through matrix sketching
I Kuzborskij, L Cella, N Cesa-Bianchi
International Conference on Artificial Intelligence and Statistics (AISTATS), 2019
162019
Distribution-Dependent Analysis of Gibbs-ERM Principle
I Kuzborskij, N Cesa-Bianchi, C Szepesvári
Conference on Learning Theory (COLT), 2019
112019
A Distribution-Dependent Analysis of Meta-Learning
M Konobeev, I Kuzborskij, C Szepesvári
International Conference on Machine Learning (ICML), 2021
7*2021
Efron-stein pac-bayesian inequalities
I Kuzborskij, C Szepesvári
arXiv preprint arXiv:1909.01931, 2019
72019
Nonparametric Online Regression while Learning the Metric
I Kuzborskij, N Cesa-Bianchi
Advances in Neural Information Processing Systems 31 (NIPS-17), 2017
72017
Theory and algorithms for hypothesis transfer learning
I Kuzborskij
EPFL, 2018
62018
On the role of optimization in double descent: A least squares study
I Kuzborskij, C Szepesvári, O Rivasplata, A Rannen-Triki, R Pascanu
In Thirty-Fifth Conference on Neural Information Processing Systems, 2021
22021
Nonparametric Regression with Shallow Overparameterized Neural Networks Trained by GD with Early Stopping
I Kuzborskij, C Szepesvári
Conference on Learning Theory (COLT), 2021
22021
Stability & Generalisation of Gradient Descent for Shallow Neural Networks without the Neural Tangent Kernel
D Richards, I Kuzborskij
Advances in Neural Information Processing Systems 33, 2021
22021
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