activity
20072026
most citedOnline Least Squares Estimation with Self-Normalized Processes: An Application to Bandit Problems

39 citations · 110 across the 23 of their papers we have counts for

collaborators

35 papers

stat.ML2026

Generalization in Nonlinear Least Squares via Learned Feature Geometry

Ayub Kharel, Ilja Kuzborskij, Patrick Rebeschini +1

We study the generalization of ridge-regularized nonlinear least-squares models via on-average algorithmic stability, deriving error bounds for local minimizers in terms of a data-…

stat.ML2026

Best of both worlds: Stochastic & adversarial best-arm identification

Yasin Abbasi-Yadkori, Peter L. Bartlett, Victor Gabillon +2

We study bandit best-arm identification with arbitrary and potentially adversarial rewards. A simple random uniform learner obtains the optimal rate of error in the adversarial sce…

cs.LG2025

Low-rank bias, weight decay, and model merging in neural networks

Ilja Kuzborskij, Yasin Abbasi Yadkori

We explore the low-rank structure of the weight matrices in neural networks at the stationary points (limiting solutions of optimization algorithms) with regularization (also…

cs.LG2024★ 3 cited

To Believe or Not to Believe Your LLM

Yasin Abbasi Yadkori, Ilja Kuzborskij, András György +1

We explore uncertainty quantification in large language models (LLMs), with the goal to identify when uncertainty in responses given a query is large. We simultaneously consider bo…

cs.LG2024★ 2 cited

Mitigating LLM Hallucinations via Conformal Abstention

Yasin Abbasi Yadkori, Ilja Kuzborskij, David Stutz +9

We develop a principled procedure for determining when a large language model (LLM) should abstain from responding (e.g., by saying "I don't know") in a general domain, instead of…

cs.LG2023

Context-lumpable stochastic bandits

Chung-Wei Lee, Qinghua Liu, Yasin Abbasi-Yadkori +3

We consider a contextual bandit problem with contexts and actions. In each round , the learner observes a random context and chooses an action based on its pas…