Matteo Ruffini | DeepAI

DeepAI AI Chat

Featured Co-authors

Guillaume Rabusseau
28 publications
Borja Balle
28 publications
Alexander Buchholz
10 publications
Giuseppe Di Benedetto
8 publications
Ben London
7 publications
Vito Bellini
6 publications
Yannik Stein
5 publications
Oriol Barbany Mayor
3 publications
Jan Malte Lichtenberg
3 publications
Ricard Gavaldà
3 publications
Fabian Moerchen
2 publications

∙ 09/03/2023

Double Clipping: Less-Biased Variance Reduction in Off-Policy Evaluation

"Clipping" (a.k.a. importance weight truncation) is a widely used varian...

0 Jan Malte Lichtenberg, et al. ∙

∙ 10/15/2022

Fair Effect Attribution in Parallel Online Experiments

A/B tests serve the purpose of reliably identifying the effect of change...

0 Alexander Buchholz, et al. ∙

∙ 05/12/2022

Low-variance estimation in the Plackett-Luce model via quasi-Monte Carlo sampling

The Plackett-Luce (PL) model is ubiquitous in learning-to-rank (LTR) bec...

0 Alexander Buchholz, et al. ∙

∙ 07/28/2021

Ranker-agnostic Contextual Position Bias Estimation

Learning-to-rank (LTR) algorithms are ubiquitous and necessary to explor...

0 Oriol Barbany Mayor, et al. ∙

∙ 10/17/2018

Hierarchical Methods of Moments

Spectral methods of moments provide a powerful tool for learning the par...

0 Matteo Ruffini, et al. ∙

∙ 07/04/2018

Generating Synthetic but Plausible Healthcare Record Datasets

Generating datasets that "look like" given real ones is an interesting t...

0 Laura Aviñó, et al. ∙

∙ 08/29/2017

Clustering Patients with Tensor Decomposition

In this paper we present a method for the unsupervised clustering of hig...

0 Matteo Ruffini, et al. ∙

Are you a researcher?
Expose your work
to one of the largest
A.I. communities in the world