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Thomas Lavastida

3 accepted papers

2024

Binary Search with Distributional Predictions

NeurIPS 2024poster

Algorithms with (machine-learned) predictions is a powerful framework for combining traditional worst-case algorithms with modern machine learning. However, the vast majority of work in this space assumes that the prediction itself is non-probabilistic, even if it is generated by some stochastic pr…

2022

Algorithms with Prediction Portfolios

NeurIPS 2022accept

The research area of algorithms with predictions has seen recent success showing how to incorporate machine learning into algorithm design to improve performance when the predictions are correct, while retaining worst-case guarantees when they are not. Most previous work has assumed that the algori…

2021

Faster Matchings via Learned Duals

NeurIPS 2021oral

A recent line of research investigates how algorithms can be augmented with machine-learned predictions to overcome worst case lower bounds. This area has revealed interesting algorithmic insights into problems, with particular success in the design of competitive online algorithms. However, the q…

Cited by 30SourcePDFScholar