Search Results for author: Alessandro Panconesi

Found 8 papers, 2 papers with code

Approximating a RUM from Distributions on k-Slates

1 code implementation22 May 2023 Flavio Chierichetti, Mirko Giacchini, Ravi Kumar, Alessandro Panconesi, Andrew Tomkins

In this work we consider the problem of fitting Random Utility Models (RUMs) to user choices.

About latent roles in forecasting players in team sports

no code implementations17 Apr 2023 Luca Scofano, Alessio Sampieri, Giuseppe Re, Matteo Almanza, Alessandro Panconesi, Fabio Galasso

Forecasting players in sports has grown in popularity due to the potential for a tactical advantage and the applicability of such research to multi-agent interaction systems.

Online Facility Location with Multiple Advice

no code implementations NeurIPS 2021 Matteo Almanza, Flavio Chierichetti, Silvio Lattanzi, Alessandro Panconesi, Giuseppe Re

Clustering is a central topic in unsupervised learning and its online formulation has received a lot of attention in recent years.

Clustering

Spectral Robustness for Correlation Clustering Reconstruction in Semi-Adversarial Models

no code implementations10 Aug 2021 Flavio Chierichetti, Alessandro Panconesi, Giuseppe Re, Luca Trevisan

We study the reconstruction version of this problem in which one is seeking to reconstruct a latent clustering that has been corrupted by random noise and adversarial modifications.

Clustering

OLIVAW: Mastering Othello without Human Knowledge, nor a Fortune

no code implementations31 Mar 2021 Antonio Norelli, Alessandro Panconesi

We introduce OLIVAW, an AI Othello player adopting the design principles of the famous AlphaGo programs.

Motivo: fast motif counting via succinct color coding and adaptive sampling

1 code implementation4 Jun 2019 Marco Bressan, Stefano Leucci, Alessandro Panconesi

To give an idea of the improvements, in $40$ minutes Motivo counts $7$-nodes motifs on a graph with $65$M nodes and $1. 8$B edges; this is $30$ and $500$ times larger than the state of the art, respectively in terms of nodes and edges.

Trainyard is NP-Hard

no code implementations2 Mar 2016 Matteo Almanza, Stefano Leucci, Alessandro Panconesi

Recently, due to the widespread diffusion of smart-phones, mobile puzzle games have experienced a huge increase in their popularity.

Computational Complexity

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