Ilja Kuzborskij

发表

Stability and Hypothesis Transfer Learning

Ilja Kuzborskij, Francesco Orabona, Francesco Orabona, 2013, ICML.

Data-Dependent Stability of Stochastic Gradient Descent

Christoph H. Lampert, Ilja Kuzborskij, Ilja Kuzborskij, 2017, ICML.

Nonparametric Online Regression while Learning the Metric

Ilja Kuzborskij, Nicolò Cesa-Bianchi, N. Cesa-Bianchi, 2017, NIPS.

PAC-Bayes Analysis Beyond the Usual Bounds pdf

Ilja Kuzborskij, Csaba Szepesvári, Omar Rivasplata, 2020, NeurIPS.

On the challenge of classifying 52 hand movements from surface electromyography

Ilja Kuzborskij, Barbara Caputo, Arjan Gijsberts, 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Supplementary Material for Data-Dependent Stability of Stochastic Gradient Descent

Christoph H. Lampert, Ilja Kuzborskij, 2018 .

When Naı̈ve Bayes Nearest Neighbors Meet Convolutional Neural Networks

Ilja Kuzborskij, Fabio Maria Carlucci, Barbara Caputo, 2015 .

PAID I TRANSFER LEARNING THROUGH GREEDY SUBSET SELECTION Ilja Kuzborskij Francesco Orabona

B. Caputo, Francesco Orabona, Ilja Kuzborskij, 2015 .

On the Role of Optimization in Double Descent: A Least Squares Study pdf

Razvan Pascanu, Ilja Kuzborskij, Csaba Szepesv'ari, 2021, NeurIPS.

Correction to “ Stability and Hypothesis Transfer Learning ”

Ilja Kuzborskij, 2014 .

Stability & Generalisation of Gradient Descent for Shallow Neural Networks without the Neural Tangent Kernel pdf

Ilja Kuzborskij, Dominic Richards, Ilja Kuzborskij, 2021, NeurIPS.

Learning Lipschitz Functions by GD-trained Shallow Overparameterized ReLU Neural Networks

Csaba Szepesvari, Ilja Kuzborskij, 2022, ArXiv.

Scalable greedy algorithms for transfer learning

Ilja Kuzborskij, Barbara Caputo, Francesco Orabona, 2014, Comput. Vis. Image Underst..

Transfer Learning Through Greedy Subset Selection pdf

Ilja Kuzborskij, Francesco Orabona, Barbara Caputo, 2014, ICIAP.

Characterization of a Benchmark Database for Myoelectric Movement Classification

Ilja Kuzborskij, Barbara Caputo, Manfredo Atzori, 2015, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

When Naïve Bayes Nearest Neighbors Meet Convolutional Neural Networks

Ilja Kuzborskij, Fabio Maria Carlucci, Barbara Caputo, 2016, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

Learning Lipschitz Functions by GD-trained Shallow Overparameterized ReLU Neural Networks

Csaba Szepesvari, Ilja Kuzborskij, 2022, ArXiv.

From N to N+1: Multiclass Transfer Incremental Learning

Ilja Kuzborskij, Barbara Caputo, Francesco Orabona, 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

Nonparametric Regression with Shallow Overparameterized Neural Networks Trained by GD with Early Stopping

Csaba Szepesvari, Ilja Kuzborskij, 2021, COLT.

Theory and Algorithms for Hypothesis Transfer Learning

Ilja Kuzborskij, Ilja Kuzborskij, 2018 .

Confident Off-Policy Evaluation and Selection through Self-Normalized Importance Weighting

Csaba Szepesvari, Claire Vernade, Ilja Kuzborskij, 2020, AISTATS.

Efron-Stein PAC-Bayesian Inequalities

Csaba Szepesvari, Ilja Kuzborskij, 2019, ArXiv.

Efficient Linear Bandits through Matrix Sketching

Ilja Kuzborskij, Nicolò Cesa-Bianchi, Leonardo Cella, 2018, AISTATS.

Distribution-Dependent Analysis of Gibbs-ERM Principle

Ilja Kuzborskij, Csaba Szepesvári, Nicolò Cesa-Bianchi, 2019, COLT.

A Distribution-dependent Analysis of Meta Learning

Ilja Kuzborskij, Csaba Szepesv'ari, Mikhail Konobeev, 2020, ICML.

Fast rates by transferring from auxiliary hypotheses

Ilja Kuzborskij, Francesco Orabona, Francesco Orabona, 2014, Machine Learning.

Learning by Transferring from Auxiliary Hypotheses pdf

Ilja Kuzborskij, Francesco Orabona, Francesco Orabona, 2014, ArXiv.

Mixture Weight Estimation and Model Prediction in Multi-source Multi-target Domain Adaptation

Ilja Kuzborskij, M. Mahdavi, Yuyang Deng, 2023, ArXiv.

On the challenge of classifying 52 hand movements from surface electromyography

B. Caputo, Ilja Kuzborskij, A. Gijsberts, 2012, Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

When Na\"ive Bayes Nearest Neighbours Meet Convolutional Neural Networks

Ilja Kuzborskij, Fabio Maria Carlucci, Barbara Caputo, 2015, 1511.03853.

Tighter PAC-Bayes Bounds Through Coin-Betting

Francesco Orabona, Ilja Kuzborskij, Kwang-Sung Jun, 2023, COLT.

Locally-Adaptive Nonparametric Online Learning pdf

Ilja Kuzborskij, Nicolo Cesa-Bianchi, N. Cesa-Bianchi, 2020, NeurIPS.

Locally-Adaptive Nonparametric Online Learning

N. Cesa-Bianchi, Ilja Kuzborskij, 2020, NeurIPS.

A Distribution-dependent Analysis of Meta Learning

Csaba Szepesvari, Ilja Kuzborskij, Mikhail Konobeev, 2020, ICML.

On Optimality of Meta-Learning in Fixed-Design Regression with Weighted Biased Regularization pdf

Ilja Kuzborskij, Csaba Szepesv'ari, Mikhail Konobeev, 2020, ArXiv.

To Believe or Not to Believe Your LLM

Yasin Abbasi-Yadkori, Ilja Kuzborskij, Csaba Szepesv'ari, 2024, ArXiv.