On the challenge of classifying 52 hand movements from surface electromyography. - Ilja Kuzborskij; Arjan Gijsberts; Barbara Caputo (EMBC, 2012)

From N to N+1: Multiclass Transfer Incremental Learning. - Ilja Kuzborskij; Francesco Orabona; Barbara Caputo (CVPR, 2013)

Stability and Hypothesis Transfer Learning. - Ilja Kuzborskij; Francesco Orabona (ICML (3), 2013)

Learning by Transferring from Auxiliary Hypotheses. - Ilja Kuzborskij; Francesco Orabona (CoRR, 2014)

Transfer Learning Through Greedy Subset Selection. - Ilja Kuzborskij; Francesco Orabona; Barbara Caputo (ICIAP (1), 2015)

When Naïve Bayes Nearest Neighbours Meet Convolutional Neural Networks. - Ilja Kuzborskij; Fabio Maria Carlucci; Barbara Caputo (CoRR, 2015)

When Naïve Bayes Nearest Neighbors Meet Convolutional Neural Networks. - Ilja Kuzborskij; Fabio Maria Carlucci; Barbara Caputo (CVPR, 2016)

Nonparametric Online Regression while Learning the Metric. - Ilja Kuzborskij; Nicolò Cesa-Bianchi (NIPS, 2017)

Scalable greedy algorithms for transfer learning. - Ilja Kuzborskij; Francesco Orabona; Barbara Caputo (Comput. Vis. Image Underst., 2017)

Fast rates by transferring from auxiliary hypotheses. - Ilja Kuzborskij; Francesco Orabona (Mach. Learn., 2017)

Data-Dependent Stability of Stochastic Gradient Descent. - Ilja Kuzborskij; Christoph H. Lampert (ICML, 2018)

Efficient Linear Bandits through Matrix Sketching. - Ilja Kuzborskij; Leonardo Cella; Nicolò Cesa-Bianchi (AISTATS, 2019)

Distribution-Dependent Analysis of Gibbs-ERM Principle. - Ilja Kuzborskij; Nicolò Cesa-Bianchi; Csaba Szepesvári (COLT, 2019)

Efron-Stein PAC-Bayesian Inequalities. - Ilja Kuzborskij; Csaba Szepesvári (CoRR, 2019)

Locally-Adaptive Nonparametric Online Learning. - Ilja Kuzborskij; Nicolò Cesa-Bianchi (NeurIPS, 2020)

PAC-Bayes Analysis Beyond the Usual Bounds. - Omar Rivasplata; Ilja Kuzborskij; Csaba Szepesvári; John Shawe-Taylor (NeurIPS, 2020)

On Optimality of Meta-Learning in Fixed-Design Regression with Weighted Biased Regularization. - Mikhail Konobeev; Ilja Kuzborskij; Csaba Szepesvári (CoRR, 2020)

Confident Off-Policy Evaluation and Selection through Self-Normalized Importance Weighting. - Ilja Kuzborskij; Claire Vernade; András György 001; Csaba Szepesvári (AISTATS, 2021)

Nonparametric Regression with Shallow Overparameterized Neural Networks Trained by GD with Early Stopping. - Ilja Kuzborskij; Csaba Szepesvári (COLT, 2021)

A Distribution-dependent Analysis of Meta Learning. - Mikhail Konobeev; Ilja Kuzborskij; Csaba Szepesvári (ICML, 2021)

On the Role of Optimization in Double Descent: A Least Squares Study. - Ilja Kuzborskij; Csaba Szepesvári; Omar Rivasplata; Amal Rannen-Triki; Razvan Pascanu (NeurIPS, 2021)

Stability & Generalisation of Gradient Descent for Shallow Neural Networks without the Neural Tangent Kernel. - Dominic Richards; Ilja Kuzborskij (NeurIPS, 2021)

Learning Lipschitz Functions by GD-trained Shallow Overparameterized ReLU Neural Networks. - Ilja Kuzborskij; Csaba Szepesvári (CoRR, 2022)

Tighter PAC-Bayes Bounds Through Coin-Betting. - Kyoungseok Jang; Kwang-Sung Jun; Ilja Kuzborskij; Francesco Orabona (COLT, 2023)

Mixture Weight Estimation and Model Prediction in Multi-source Multi-target Domain Adaptation. - Yuyang Deng; Ilja Kuzborskij; Mehrdad Mahdavi (NeurIPS, 2023)

Better-than-KL PAC-Bayes Bounds. - Ilja Kuzborskij; Kwang-Sung Jun; Yulian Wu; Kyoungseok Jang; Francesco Orabona (COLT, 2024)

To Believe or Not to Believe Your LLM: Iterative Prompting for Estimating Epistemic Uncertainty. - Yasin Abbasi-Yadkori; Ilja Kuzborskij; András György 001; Csaba Szepesvári (NeurIPS, 2024)

Mitigating LLM Hallucinations via Conformal Abstention. - Yasin Abbasi-Yadkori; Ilja Kuzborskij; David Stutz; András György 001; Adam Fisch; Arnaud Doucet; Iuliya Beloshapka; Wei-Hung Weng; Yao-Yuan Yang; Csaba Szepesvári; Ali Taylan Cemgil; Nenad Tomasev (CoRR, 2024)

To Believe or Not to Believe Your LLM. - Yasin Abbasi-Yadkori; Ilja Kuzborskij; András György 001; Csaba Szepesvári (CoRR, 2024)

Low-rank bias, weight decay, and model merging in neural networks. - Ilja Kuzborskij; Yasin Abbasi-Yadkori (CoRR, 2025)

Pointwise confidence estimation in the non-linear ℓ2-regularized least squares. - Ilja Kuzborskij; Yasin Abbasi-Yadkori (CoRR, 2025)