Ilja Kuzborskij

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Barbara CaputoDAUIN, Politecnico di TorinoVerified email at polito.it
Francesco OrabonaAssociate Professor, KAUSTVerified email at orabona.com
Csaba SzepesvariDeepMind & University of AlbertaVerified email at cs.ualberta.ca
Arjan GijsbertsItalian Institute of TechnologyVerified email at iit.it
Claudio CastelliniProfessor of Medical Robotics at FAU Erlangen and senior researcher at the German Aerospace CenterVerified email at fau.de
Henning MüllerProfessor in computer science at HES-SO & in radiology at the University of GenevaVerified email at hevs.ch
Manfredo AtzoriHESSO Valais, University of PadovaVerified email at hevs.ch
Nicolò Cesa-BianchiProfessor of Computer Science, Università degli Studi di Milano and Politecnico di MilanoVerified email at unimi.it
Simone ElsigUniversity of Applied Sciences and Arts Western Switzerland Valais (HES-SO Valais-Wallis)Verified email at hevs.ch
Christoph H. LampertInstitute of Science and Technology Austria (ISTA)Verified email at ist.ac.at
John Shawe-TaylorUCLVerified email at cs.ucl.ac.uk
Claire VernadeUniversity of TuebingenVerified email at uni-tuebingen.de
Andras GyorgyDeepMindVerified email at google.com
Fabio Maria CarlucciMetaVerified email at meta.com
Leonardo CellaData Scientist @ AxpoVerified email at iit.it
Dominic RichardsPHD Student, University of OxfordVerified email at spc.ox.ac.uk
Amal Rannen TrikiResearch Scientist at DeepMindVerified email at google.com
Razvan PascanuResearch Scientist at Google DeepMindVerified email at google.com
Kwang-Sung JunThe University of ArizonaVerified email at cs.arizona.edu
Kyoungseok JangNew York UniversityVerified email at nyu.edu

Ilja Kuzborskij

Google DeepMind

Verified email at google.com - Homepage

Machine Learning Learning Theory


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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	268	2014
Stability and hypothesis transfer learning I Kuzborskij, F Orabona International Conference on Machine Learning, 942-950, 2013	184	2013
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	160	2013
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	147	2012
Data-Dependent Stability of Stochastic Gradient Descent I Kuzborskij, CH Lampert International Conference on Machine Learning, 2018	141	2018
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	67	2020
Fast Rates by Transferring from Auxiliary Hypotheses I Kuzborskij, F Orabona Machine Learning, 2016	65	2016
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	39	2021
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	30	2016
Transfer Learning through Greedy Subset Selection I Kuzborskij, B Caputo, F Orabona 18th International Conference on Image Analysis and Processing — ICIAP 2015, 2015	26	2015
Scalable greedy algorithms for transfer learning I Kuzborskij, F Orabona, B Caputo Computer Vision and Image Understanding 156, 174-185, 2017	20	2017
Efficient linear bandits through matrix sketching I Kuzborskij, L Cella, N Cesa-Bianchi International Conference on Artificial Intelligence and Statistics (AISTATS), 2019	19	2019
Efron-stein pac-bayesian inequalities I Kuzborskij, C Szepesvári arXiv preprint arXiv:1909.01931, 2019	18	2019
Distribution-Dependent Analysis of Gibbs-ERM Principle I Kuzborskij, N Cesa-Bianchi, C Szepesvári Conference on Learning Theory (COLT), 2019	16	2019
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	15	2021
A Distribution-Dependent Analysis of Meta-Learning M Konobeev, I Kuzborskij, C Szepesvári International Conference on Machine Learning (ICML), 2021	14*	2021
Theory and algorithms for hypothesis transfer learning I Kuzborskij EPFL, 2018	9	2018
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	8	2021
Nonparametric Online Regression while Learning the Metric I Kuzborskij, N Cesa-Bianchi Advances in Neural Information Processing Systems 31 (NIPS-17), 2017	8	2017
Learning Lipschitz Functions by GD-trained Shallow Overparameterized ReLU Neural Networks I Kuzborskij, C Szepesvári arXiv preprint arXiv:2212.13848, 2022	7*	2022

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