Ilja Kuzborskij
Ilja Kuzborskij
DeepMind
Verified email at google.com - Homepage
TitleCited byYear
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
882014
From n to n+ 1: Multiclass transfer incremental learning
I Kuzborskij, F Orabona, B Caputo
Proceedings of the IEEE Conference on Computer Vision and Patterná…, 2013
802013
Stability and hypothesis transfer learning
I Kuzborskij, F Orabona
International Conference on Machine Learning, 942-950, 2013
772013
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 andá…, 2012
722012
Fast Rates by Transferring from Auxiliary Hypotheses
I Kuzborskij, F Orabona
Machine Learning, 2016
262016
Data-Dependent Stability of Stochastic Gradient Descent
I Kuzborskij, CH Lampert
International Conference on Machine Learning, 2018
252018
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
162016
Transfer Learning through Greedy Subset Selection
I Kuzborskij, B Caputo, F Orabona
18th International Conference on Image Analysis and Processing — ICIAP 2015, 2015
142015
Scalable greedy algorithms for transfer learning
I Kuzborskij, F Orabona, B Caputo
Computer Vision and Image Understanding 156, 174-185, 2017
132017
Nonparametric Online Regression while Learning the Metric
I Kuzborskij, N Cesa-Bianchi
Advances in Neural Information Processing Systems 31 (NIPS-17), 2017
32017
Efficient linear bandits through matrix sketching
I Kuzborskij, L Cella, N Cesa-Bianchi
International Conference on Artificial Intelligence and Statistics (AISTATS), 2019
12019
Theory and Algorithms for Hypothesis Transfer Learning
I Kuzborskij
EPFL, 2018
12018
Distribution-Dependent Analysis of Gibbs-ERM Principle
I Kuzborskij, N Cesa-Bianchi, C Szepesvßri
Conference on Learning Theory (COLT), 2019
2019
Supplementary Material for Data-Dependent Stability of Stochastic Gradient Descent
I Kuzborskij, CH Lampert
Supplementary Material for “Nonparametric Online Regression while Learning the Metric”
I Kuzborskij, N Cesa-Bianchi
Correction to “Stability and Hypothesis Transfer Learning”
I Kuzborskij, F Orabona
The system can't perform the operation now. Try again later.
Articles 1–16