3 citations · 4 across the 4 of their papers we have counts for
6 papers
Predicting Drafted Deck Strength for "Magic: the Gathering"
Tomas Rigaux, Hisashi Kashima
Many real-world games do not admit a fixed, compact rule set: instead, their dynamics are defined by interactions among a large and often evolving collection of game pieces, making…
Adaptive Quality-Diversity Trade-offs for Large-Scale Batch Recommendation
Clémence Réda, Tomas Rigaux, Hiba Bederina +3
A core research question in recommender systems is to propose batches of highly relevant and diverse items, that is, items personalized to the user's preferences, but which also mi…
Enhancing Chess Reinforcement Learning with Graph Representation
Tomas Rigaux, Hisashi Kashima
Mastering games is a hard task, as games can be extremely complex, and still fundamentally different in structure from one another. While the AlphaZero algorithm has demonstrated a…
Variational Factorization Machines for Preference Elicitation in Large-Scale Recommender Systems
Jill-Jênn Vie, Tomas Rigaux, Hisashi Kashima
Factorization machines (FMs) are a powerful tool for regression and classification in the context of sparse observations, that has been successfully applied to collaborative filter…
Privacy-Preserving Synthetic Educational Data Generation
Jill-Jênn Vie, Tomas Rigaux, Sein Minn
Institutions collect massive learning traces but they may not disclose it for privacy issues. Synthetic data generation opens new opportunities for research in education. In this p…
Algorithmic Meta-Theorems for Monotone Submodular Maximization
Masakazu Ishihata, Takanori Maehara, Tomas Rigaux
We consider a monotone submodular maximization problem whose constraint is described by a logic formula on a graph. Formally, we prove the following three `algorithmic metatheorems…