Abstract. Reinforcement learning (RL) is a widely used learning paradigm for adaptive agents. There exist several convergent and consistent RL algorithms which have been intensivel...
Lucian Busoniu, Damien Ernst, Bart De Schutter, Ro...
In this paper, we propose a new and general preprocessor algorithm, called CSRoulette, which converts any cost-insensitive classification algorithms into cost-sensitive ones. CSRou...
Classification of data with imbalanced class distribution has posed a significant drawback of the performance attainable by most standard classifier learning algorithms, which ...
Abstract. Different strategies to learn user semantic queries from dissimilarity representations of video audio-visual content are presented. When dealing with large corpora of vi...
Information extraction is concerned with applying natural language processing to automatically extract the essential details from text documents. A great disadvantage of current ap...