Most recommender systems present recommended products in lists to the user. By doing so, much information is lost about the mutual similarity between recommended products. We prop...
Martijn Kagie, Michiel C. van Wezel, Patrick J. F....
Given the ubiquity of time series data, the data mining community has spent significant time investigating the best time series similarity measure to use for various tasks and dom...
Qiang Zhu 0002, Gustavo E. A. P. A. Batista, Thana...
The success ofreinforcement learninginpractical problems depends on the ability to combine function approximation with temporal di erence methods such as value iteration. Experime...
In this paper we introduce “clipping,” a new method of syntactic approximation which is motivated by and works in conjunction with a sound and decidable denotational model for...
Approximate Linear Programming (ALP) is a reinforcement learning technique with nice theoretical properties, but it often performs poorly in practice. We identify some reasons for...