Reinforcement learning is an effective machine learning paradigm in domains represented by compact and discrete state-action spaces. In high-dimensional and continuous domains, ti...
Abstract. Previous researches on advanced representations for document retrieval have shown that statistical state-of-the-art models are not improved by a variety of different ling...
Abstract. The last years there is an increasing interest for query processing techniques that take into consideration the dominance relationship between objects to select the most ...
Eleftherios Tiakas, Apostolos N. Papadopoulos, Yan...
Abstract: The Principal Component Analysis (PCA) is a data dimensionality reduction technique well-suited for processing data from sensor networks. It can be applied to tasks like ...
Abstract: This paper presents a novel approach for object classification and pose estimation which employs spherical light field rendering to generate virtual views based on synthe...