collaborators

7 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-…

cs.LG2026

On-Average Stability of Multipass Preconditioned SGD and Effective Dimension

Simon Vary, Tyler Farghly, Ilja Kuzborskij +1

We study trade-offs between the population risk curvature, geometry of the noise, and preconditioning on the generalisation ability of the multipass Preconditioned Stochastic Gradi…

cs.AI2026

DAG-Math: Graph-of-Thought Guided Mathematical Reasoning in LLMs

Yuanhe Zhang, Ilja Kuzborskij, Jason D. Lee +2

Large Language Models (LLMs) demonstrate strong performance on mathematical problems when prompted with Chain-of-Thought (CoT), yet it remains unclear whether this success stems fr…

cs.LG2026

Sufficient Conditions for Stability of Minimum-Norm Interpolating Deep ReLU Networks

Ouns El Harzli, Yoonsoo Nam, Ilja Kuzborskij +2

Algorithmic stability is a classical framework for analyzing the generalization error of learning algorithms. It predicts that an algorithm has small generalization error if it is…

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.LG2025

Pointwise confidence estimation in the non-linear -regularized least squares

Ilja Kuzborskij, Yasin Abbasi Yadkori

We consider a high-probability non-asymptotic confidence estimation in the -regularized non-linear least-squares setting with fixed design. In particular, we study confiden…