In the music information retrieval field, the most important topic is to extract the feature which represents the content from the music objects. The content feature is useful for ...
In this paper, we investigate the use of parallelization in reinforcement learning (RL), with the goal of learning optimal policies for single-agent RL problems more quickly by us...
In research on musical audio-mining, annotated music databases are needed which allow the development of computational tools that extract from the musical audiostream the kind of ...
Micheline Lesaffre, Marc Leman, Bernard De Baets, ...
To access data sources on the Web, a crucial step is wrapping, which translates query responses, rendered in textual HTML, back into their relational form. Traditionally, this pro...
Shui-Lung Chuang, Kevin Chen-Chuan Chang, ChengXia...
Planning in single-agent models like MDPs and POMDPs can be carried out by resorting to Q-value functions: a (near-) optimal Q-value function is computed in a recursive manner by ...