Ilja Kuzborskij

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 37

Top Topics

Nonparametric Regression

Subset Selection

Top Venues

Publications

Yasin Abbasi-Yadkori, Ilja Kuzborskij, András György, Csaba Szepesvári
To Believe or Not to Believe Your LLM. CoRR (2024)
Ilja Kuzborskij, Kwang-Sung Jun, Yulian Wu, Kyoungseok Jang, Francesco Orabona
Better-than-KL PAC-Bayes Bounds. COLT (2024)
Ilja Kuzborskij, Kwang-Sung Jun, Yulian Wu, Kyoungseok Jang, Francesco Orabona
Better-than-KL PAC-Bayes Bounds. CoRR (2024)
Yasin Abbasi-Yadkori, Ilja Kuzborskij, David Stutz, András György, Adam Fisch, Arnaud Doucet, Iuliya Beloshapka, Wei-Hung Weng, Yao-Yuan Yang, Csaba Szepesvári, Ali Taylan Cemgil, Nenad Tomasev
Mitigating LLM Hallucinations via Conformal Abstention. CoRR (2024)
Yuyang Deng, Ilja Kuzborskij, Mehrdad Mahdavi
Mixture Weight Estimation and Model Prediction in Multi-source Multi-target Domain Adaptation. CoRR (2023)
Yuyang Deng, Ilja Kuzborskij, Mehrdad Mahdavi
Mixture Weight Estimation and Model Prediction in Multi-source Multi-target Domain Adaptation. NeurIPS (2023)
Kyoungseok Jang, Kwang-Sung Jun, Ilja Kuzborskij, Francesco Orabona
Tighter PAC-Bayes Bounds Through Coin-Betting. COLT (2023)
Kyoungseok Jang, Kwang-Sung Jun, Ilja Kuzborskij, Francesco Orabona
Tighter PAC-Bayes Bounds Through Coin-Betting. CoRR (2023)
Ilja Kuzborskij, Csaba Szepesvári
Learning Lipschitz Functions by GD-trained Shallow Overparameterized ReLU Neural Networks. CoRR (2022)
Ilja Kuzborskij, Csaba Szepesvári, Omar Rivasplata, Amal Rannen Triki, Razvan Pascanu
On the Role of Optimization in Double Descent: A Least Squares Study. CoRR (2021)
Ilja Kuzborskij, Csaba Szepesvári
Nonparametric Regression with Shallow Overparameterized Neural Networks Trained by GD with Early Stopping. CoRR (2021)
Ilja Kuzborskij, Claire Vernade, András György, Csaba Szepesvári
Confident Off-Policy Evaluation and Selection through Self-Normalized Importance Weighting. AISTATS (2021)
Ilja Kuzborskij, Csaba Szepesvári
Nonparametric Regression with Shallow Overparameterized Neural Networks Trained by GD with Early Stopping. COLT (2021)
Dominic Richards, Ilja Kuzborskij
Stability & Generalisation of Gradient Descent for Shallow Neural Networks without the Neural Tangent Kernel. CoRR (2021)
Mikhail Konobeev, Ilja Kuzborskij, Csaba Szepesvári
A Distribution-dependent Analysis of Meta Learning. ICML (2021)
Dominic Richards, Ilja Kuzborskij
Stability & Generalisation of Gradient Descent for Shallow Neural Networks without the Neural Tangent Kernel. NeurIPS (2021)
Ilja Kuzborskij, Csaba Szepesvári, Omar Rivasplata, Amal Rannen-Triki, Razvan Pascanu
On the Role of Optimization in Double Descent: A Least Squares Study. NeurIPS (2021)
Ilja Kuzborskij, Nicolò Cesa-Bianchi
Locally-Adaptive Nonparametric Online Learning. CoRR (2020)
Ilja Kuzborskij, Claire Vernade, András György, Csaba Szepesvári
Confident Off-Policy Evaluation and Selection through Self-Normalized Importance Weighting. CoRR (2020)
Ilja Kuzborskij, Nicolò Cesa-Bianchi
Locally-Adaptive Nonparametric Online Learning. NeurIPS (2020)
Omar Rivasplata, Ilja Kuzborskij, Csaba Szepesvári, John Shawe-Taylor
PAC-Bayes Analysis Beyond the Usual Bounds. CoRR (2020)
Omar Rivasplata, Ilja Kuzborskij, Csaba Szepesvári, John Shawe-Taylor
PAC-Bayes Analysis Beyond the Usual Bounds. NeurIPS (2020)
Mikhail Konobeev, Ilja Kuzborskij, Csaba Szepesvári
On Optimality of Meta-Learning in Fixed-Design Regression with Weighted Biased Regularization. CoRR (2020)
Ilja Kuzborskij, Csaba Szepesvári
Efron-Stein PAC-Bayesian Inequalities. CoRR (2019)
Ilja Kuzborskij, Leonardo Cella, Nicolò Cesa-Bianchi
Efficient Linear Bandits through Matrix Sketching. AISTATS (2019)
Ilja Kuzborskij, Nicolò Cesa-Bianchi, Csaba Szepesvári
Distribution-Dependent Analysis of Gibbs-ERM Principle. COLT (2019)
Ilja Kuzborskij, Nicolò Cesa-Bianchi, Csaba Szepesvári
Distribution-Dependent Analysis of Gibbs-ERM Principle. CoRR (2019)
Ilja Kuzborskij, Christoph H. Lampert
Data-Dependent Stability of Stochastic Gradient Descent. ICML (2018)
Ilja Kuzborskij, Leonardo Cella, Nicolò Cesa-Bianchi
Efficient Linear Bandits through Matrix Sketching. CoRR (2018)
Ilja Kuzborskij, Christoph H. Lampert
Data-Dependent Stability of Stochastic Gradient Descent. CoRR (2017)
Ilja Kuzborskij, Nicolò Cesa-Bianchi
Nonparametric Online Regression while Learning the Metric. CoRR (2017)
Ilja Kuzborskij, Francesco Orabona
Fast rates by transferring from auxiliary hypotheses. Mach. Learn. 106 (2) (2017)
Ilja Kuzborskij, Nicolò Cesa-Bianchi
Nonparametric Online Regression while Learning the Metric. NIPS (2017)
Ilja Kuzborskij, Francesco Orabona, Barbara Caputo
Scalable greedy algorithms for transfer learning. Comput. Vis. Image Underst. 156 (2017)
Ilja Kuzborskij, Fabio Maria Carlucci, Barbara Caputo
When Naïve Bayes Nearest Neighbors Meet Convolutional Neural Networks. CVPR (2016)
Ilja Kuzborskij, Francesco Orabona, Barbara Caputo
Transfer Learning Through Greedy Subset Selection. ICIAP (1) (2015)
Ilja Kuzborskij, Fabio Maria Carlucci, Barbara Caputo
When Naïve Bayes Nearest Neighbours Meet Convolutional Neural Networks. CoRR (2015)
Ilja Kuzborskij, Barbara Caputo, Francesco Orabona
Transfer Learning through Greedy Subset Selection. CoRR (2014)
Ilja Kuzborskij, Francesco Orabona
Learning by Transferring from Auxiliary Hypotheses. CoRR (2014)
Ilja Kuzborskij, Francesco Orabona, Barbara Caputo
From N to N+1: Multiclass Transfer Incremental Learning. CVPR (2013)
Ilja Kuzborskij, Francesco Orabona
Stability and Hypothesis Transfer Learning. ICML (3) (2013)
Ilja Kuzborskij, Arjan Gijsberts, Barbara Caputo
On the challenge of classifying 52 hand movements from surface electromyography. EMBC (2012)