Abstract. Learning To Rank (LTR) techniques aim to learn an effective document ranking function by combining several document features. While the function learned may be uniformly ...
This paper presents a supervised manifold learning model for dimensionality reduction in image and video classification tasks. Unlike most manifold learning models that emphasize ...
Reinforcement Learning (RL) is the study of programs that improve their performance by receiving rewards and punishments from the environment. Most RL methods optimize the discoun...
This paper presents a cooperative evolutionary approach for the problem of instance selection for instance based learning. The presented model takes advantage of one of the most r...
We discuss vision as a sensory modality for systems that effect actions in response to perceptions. While the internal representations informed by vision may be arbitrarily compl...