Ilja Kuzborskij

47 papers A* 14A 2Journal 27Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	On-Average Stability of Multipass Preconditioned SGD and Effective Dimension. CoRR Simon Vary, Tyler Farghly, Ilja Kuzborskij, Patrick Rebeschini
2026	J	`jnl`	Sufficient Conditions for Stability of Minimum-Norm Interpolating Deep ReLU Networks. CoRR Ouns El Harzli, Yoonsoo Nam, Ilja Kuzborskij, Bernardo Cuenca Grau, Ard A. Louis
2025	J	`jnl`	DAG-Math: Graph-Guided Mathematical Reasoning in LLMs. CoRR Yuanhe Zhang, Ilja Kuzborskij, Jason D. Lee, Chenlei Leng, Fanghui Liu
2025	J	`jnl`	Low-rank bias, weight decay, and model merging in neural networks. CoRR Ilja Kuzborskij, Yasin Abbasi-Yadkori
2025	J	`jnl`	Pointwise confidence estimation in the non-linear ℓ CoRR Ilja Kuzborskij, Yasin Abbasi-Yadkori
2024	A*	`conf`	Better-than-KL PAC-Bayes Bounds. COLT Ilja Kuzborskij, Kwang-Sung Jun, Yulian Wu, Kyoungseok Jang, Francesco Orabona
2024	J	`jnl`	Better-than-KL PAC-Bayes Bounds. CoRR Ilja Kuzborskij, Kwang-Sung Jun, Yulian Wu, Kyoungseok Jang, Francesco Orabona
2024	J	`jnl`	Mitigating LLM Hallucinations via Conformal Abstention. CoRR 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
2024	J	`jnl`	To Believe or Not to Believe Your LLM. CoRR Yasin Abbasi-Yadkori, Ilja Kuzborskij, András György, Csaba Szepesvári
2024	A*	`conf`	To Believe or Not to Believe Your LLM: Iterative Prompting for Estimating Epistemic Uncertainty. NeurIPS Yasin Abbasi-Yadkori, Ilja Kuzborskij, András György, Csaba Szepesvári
2023	A*	`conf`	Mixture Weight Estimation and Model Prediction in Multi-source Multi-target Domain Adaptation. NeurIPS Yuyang Deng, Ilja Kuzborskij, Mehrdad Mahdavi
2023	J	`jnl`	Mixture Weight Estimation and Model Prediction in Multi-source Multi-target Domain Adaptation. CoRR Yuyang Deng, Ilja Kuzborskij, Mehrdad Mahdavi
2023	A*	`conf`	Tighter PAC-Bayes Bounds Through Coin-Betting. COLT Kyoungseok Jang, Kwang-Sung Jun, Ilja Kuzborskij, Francesco Orabona
2023	J	`jnl`	Tighter PAC-Bayes Bounds Through Coin-Betting. CoRR Kyoungseok Jang, Kwang-Sung Jun, Ilja Kuzborskij, Francesco Orabona
2022	J	`jnl`	Learning Lipschitz Functions by GD-trained Shallow Overparameterized ReLU Neural Networks. CoRR Ilja Kuzborskij, Csaba Szepesvári
2021	A*	`conf`	A Distribution-dependent Analysis of Meta Learning. ICML Mikhail Konobeev, Ilja Kuzborskij, Csaba Szepesvári
2021	A	`conf`	Confident Off-Policy Evaluation and Selection through Self-Normalized Importance Weighting. AISTATS Ilja Kuzborskij, Claire Vernade, András György, Csaba Szepesvári
2021	A*	`conf`	Nonparametric Regression with Shallow Overparameterized Neural Networks Trained by GD with Early Stopping. COLT Ilja Kuzborskij, Csaba Szepesvári
2021	A*	`conf`	On the Role of Optimization in Double Descent: A Least Squares Study. NeurIPS Ilja Kuzborskij, Csaba Szepesvári, Omar Rivasplata, Amal Rannen-Triki, Razvan Pascanu
2021	J	`jnl`	On the Role of Optimization in Double Descent: A Least Squares Study. CoRR Ilja Kuzborskij, Csaba Szepesvári, Omar Rivasplata, Amal Rannen-Triki, Razvan Pascanu
2021	A*	`conf`	Stability & Generalisation of Gradient Descent for Shallow Neural Networks without the Neural Tangent Kernel. NeurIPS Dominic Richards, Ilja Kuzborskij
2021	J	`jnl`	Stability & Generalisation of Gradient Descent for Shallow Neural Networks without the Neural Tangent Kernel. CoRR Dominic Richards, Ilja Kuzborskij
2020	J	`jnl`	Confident Off-Policy Evaluation and Selection through Self-Normalized Importance Weighting. CoRR Ilja Kuzborskij, Claire Vernade, András György, Csaba Szepesvári
2020	A*	`conf`	Locally-Adaptive Nonparametric Online Learning. NeurIPS Ilja Kuzborskij, Nicolò Cesa-Bianchi
2020	J	`jnl`	Locally-Adaptive Nonparametric Online Learning. CoRR Ilja Kuzborskij, Nicolò Cesa-Bianchi
2020	J	`jnl`	On Optimality of Meta-Learning in Fixed-Design Regression with Weighted Biased Regularization. CoRR Mikhail Konobeev, Ilja Kuzborskij, Csaba Szepesvári
2020	A*	`conf`	PAC-Bayes Analysis Beyond the Usual Bounds. NeurIPS Omar Rivasplata, Ilja Kuzborskij, Csaba Szepesvári, John Shawe-Taylor
2020	J	`jnl`	PAC-Bayes Analysis Beyond the Usual Bounds. CoRR Omar Rivasplata, Ilja Kuzborskij, Csaba Szepesvári, John Shawe-Taylor
2019	A*	`conf`	Distribution-Dependent Analysis of Gibbs-ERM Principle. COLT Ilja Kuzborskij, Nicolò Cesa-Bianchi, Csaba Szepesvári
2019	J	`jnl`	Distribution-Dependent Analysis of Gibbs-ERM Principle. CoRR Ilja Kuzborskij, Nicolò Cesa-Bianchi, Csaba Szepesvári
2019	A	`conf`	Efficient Linear Bandits through Matrix Sketching. AISTATS Ilja Kuzborskij, Leonardo Cella, Nicolò Cesa-Bianchi
2019	J	`jnl`	Efron-Stein PAC-Bayesian Inequalities. CoRR Ilja Kuzborskij, Csaba Szepesvári
2018	A*	`conf`	Data-Dependent Stability of Stochastic Gradient Descent. ICML Ilja Kuzborskij, Christoph H. Lampert
2018	J	`jnl`	Efficient Linear Bandits through Matrix Sketching. CoRR Ilja Kuzborskij, Leonardo Cella, Nicolò Cesa-Bianchi
2017	J	`jnl`	Data-Dependent Stability of Stochastic Gradient Descent. CoRR Ilja Kuzborskij, Christoph H. Lampert
2017	J	`jnl`	Fast rates by transferring from auxiliary hypotheses. Mach. Learn. Ilja Kuzborskij, Francesco Orabona
2017	—	`conf`	Nonparametric Online Regression while Learning the Metric. NIPS Ilja Kuzborskij, Nicolò Cesa-Bianchi
2017	J	`jnl`	Nonparametric Online Regression while Learning the Metric. CoRR Ilja Kuzborskij, Nicolò Cesa-Bianchi
2017	J	`jnl`	Scalable greedy algorithms for transfer learning. Comput. Vis. Image Underst. Ilja Kuzborskij, Francesco Orabona, Barbara Caputo
2016	A*	`conf`	When Naïve Bayes Nearest Neighbors Meet Convolutional Neural Networks. CVPR Ilja Kuzborskij, Fabio Maria Carlucci, Barbara Caputo
2015	—	`conf`	Transfer Learning Through Greedy Subset Selection. ICIAP (1) Ilja Kuzborskij, Francesco Orabona, Barbara Caputo
2015	J	`jnl`	When Naïve Bayes Nearest Neighbours Meet Convolutional Neural Networks. CoRR Ilja Kuzborskij, Fabio Maria Carlucci, Barbara Caputo
2014	J	`jnl`	Learning by Transferring from Auxiliary Hypotheses. CoRR Ilja Kuzborskij, Francesco Orabona
2014	J	`jnl`	Transfer Learning through Greedy Subset Selection. CoRR Ilja Kuzborskij, Barbara Caputo, Francesco Orabona
2013	A*	`conf`	From N to N+1: Multiclass Transfer Incremental Learning. CVPR Ilja Kuzborskij, Francesco Orabona, Barbara Caputo
2013	—	`conf`	Stability and Hypothesis Transfer Learning. ICML (3) Ilja Kuzborskij, Francesco Orabona
2012	—	`conf`	On the challenge of classifying 52 hand movements from surface electromyography. EMBC Ilja Kuzborskij, Arjan Gijsberts, Barbara Caputo