Alessandro Rudi

NYTRO: When Subsampling Meets Early Stopping

2016 · CINECA IRIS Institutial Research Information System (University of Genoa)

Early stopping is a well known approach to reduce the time complexity for performing training and model selection of large scale learning machines. On the other hand, memory/space (rather than time) complexity is the main …

Structured Prediction with Partial Labelling through the Infimum Loss

2020 · arXiv (Cornell University)

Annotating datasets is one of the main costs in nowadays supervised learning. The goal of weak supervision is to enable models to learn using only forms of labelling which are cheaper to collect, as partial …

Super fast rates in structured prediction

2021 · arXiv (Cornell University)

Discrete supervised learning problems such as classification are often tackled by introducing a continuous surrogate problem akin to regression. Bounding the original error, between estimate and solution, by the surrogate error endows discrete problems with …