papers

Publications (49)

cs.IT2014

Phaseless Signal Recovery in Infinite Dimensional Spaces using Structured Modulations

Volker Pohl, Fanny Yang, Holger Boche

This paper considers the recovery of continuous signals in infinite dimensional spaces from the magnitude of their frequency samples. It proposes a sampling scheme which involves a…

cs.LG2023

Can semi-supervised learning use all the data effectively? A lower bound perspective

Alexandru Ţifrea, Gizem Yüce, Amartya Sanyal +1

Prior works have shown that semi-supervised learning algorithms can leverage unlabeled data to improve over the labeled sample complexity of supervised learning (SL) algorithms. Ho…

stat.ML2018

Early stopping for kernel boosting algorithms: A general analysis with localized complexities

Yuting Wei, Fanny Yang, Martin J. Wainwright

Early stopping of iterative algorithms is a widely-used form of regularization in statistics, commonly used in conjunction with boosting and related gradient-type algorithms. Altho…

stat.ME2026

Detecting critical treatment effect bias in small subgroups

Piersilvio De Bartolomeis, Javier Abad, Konstantin Donhauser +1

Randomized trials are considered the gold standard for making informed decisions in medicine, yet they often lack generalizability to the patient populations in clinical practice.…

cs.SD2026

WavFlow: Audio Generation in Waveform Space

Feiyan Zhou, Luyuan Wang, Shoufa Chen +6

Modern audio generation predominantly relies on latent-space compression, introducing additional complexity and potential information loss. In this work, we challenge this paradigm…

stat.ML2026

Doubly robust identification of treatment effects from multiple environments

Piersilvio De Bartolomeis, Julia Kostin, Javier Abad +2

Practical and ethical constraints often require the use of observational data for causal inference, particularly in medicine and social sciences. Yet, observational datasets are pr…