The current framework of reinforcement learning is based on maximizing the expected returns based on scalar rewards. But in many real world situations, tradeoffs must be made amon...
We consider the problem of online learning in a changing environment under sparse user feedback. Specifically, we address the classification of music types according to a user...
Highly distributed systems such as Grids are used today to the execution of large-scale parallel applications. The behavior analysis of these applications is not trivial. The comp...
Lucas Mello Schnorr, Guillaume Huard, Philippe Oli...
This paper presents an innovative partitionbased time join strategy for temporal databases where time is represented by time intervals. The proposed method maps time intervals to ...
A recommender system suggests the items expected to be preferred by the users. Recommender systems use collaborative filtering to recommend items by summarizing the preferences of...