Lenka Zdeborová

Probing transfer learning with a model of synthetic correlated datasets

2022 · Machine Learning Science and Technology

Abstract Transfer learning can significantly improve the sample efficiency of neural networks, by exploiting the relatedness between a data-scarce target task and a data-abundant source task. Despite years of successful applications, transfer learning practice often …

Learning curves of generic features maps for realistic datasets with a teacher-student model

2021 · Infoscience (Ecole Polytechnique Fédérale de Lausanne)

Teacher-student models provide a framework in which the typical-case performance of high-dimensional supervised learning can be described in closed form. The assumptions of Gaussian i.i.d. input data underlying the canonical teacher-student model may, however, be …

Fundamental computational limits of weak learnability in high-dimensional multi-index models

2024 · arXiv (Cornell University)

Multi-index models - functions which only depend on the covariates through a non-linear transformation of their projection on a subspace - are a useful benchmark for investigating feature learning with neural nets. This paper examines …

Computational Thresholds in Multi-Modal Learning via the Spiked Matrix-Tensor Model

2025 · arXiv (Cornell University)

We study the recovery of multiple high-dimensional signals from two noisy, correlated modalities: a spiked matrix and a spiked tensor sharing a common low-rank structure. This setting generalizes classical spiked matrix and tensor models, unveiling …