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Ilja Kuzborskij
Ilja Kuzborskij
Google 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
3122014
Stability and hypothesis transfer learning
I Kuzborskij, F Orabona
International Conference on Machine Learning, 942-950, 2013
2072013
Data-Dependent Stability of Stochastic Gradient Descent
I Kuzborskij, CH Lampert
International Conference on Machine Learning, 2018
1712018
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
1712013
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
1652012
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
912020
Fast Rates by Transferring from Auxiliary Hypotheses
I Kuzborskij, F Orabona
Machine Learning, 2016
732016
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
492021
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
342016
Tighter PAC-Bayes Bounds Through Coin-Betting
K Jang, KS Jun, I Kuzborskij, F Orabona
Conference on Learning Theory (COLT), 2023
282023
Transfer Learning through Greedy Subset Selection
I Kuzborskij, B Caputo, F Orabona
18th International Conference on Image Analysis and Processing — ICIAP 2015, 2015
282015
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
252021
Efron-stein pac-bayesian inequalities
I Kuzborskij, C Szepesvári
arXiv preprint arXiv:1909.01931, 2019
232019
Efficient linear bandits through matrix sketching
I Kuzborskij, L Cella, N Cesa-Bianchi
International Conference on Artificial Intelligence and Statistics (AISTATS), 2019
222019
Scalable greedy algorithms for transfer learning
I Kuzborskij, F Orabona, B Caputo
Computer Vision and Image Understanding 156, 174-185, 2017
212017
Distribution-Dependent Analysis of Gibbs-ERM Principle
I Kuzborskij, N Cesa-Bianchi, C Szepesvári
Conference on Learning Theory (COLT), 2019
192019
To Believe or Not to Believe Your LLM
YA Yadkori, I Kuzborskij, A György, C Szepesvári
Conference on Neural Information Processing Systems (NeurIPS), 2024
172024
A Distribution-Dependent Analysis of Meta-Learning
M Konobeev, I Kuzborskij, C Szepesvári
International Conference on Machine Learning (ICML), 2021
15*2021
Learning lipschitz functions by gd-trained shallow overparameterized relu neural networks
I Kuzborskij, C Szepesvári
arXiv preprint arXiv:2212.13848, 2022
14*2022
On the role of optimization in double descent: A least squares study
I Kuzborskij, C Szepesvári, O Rivasplata, A Rannen-Triki, R Pascanu
Conference on Neural Information Processing Systems (NeurIPS), 2021
142021
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