In this work, we study the problem of within-network relational learning and inference, where models are learned on a partially labeled relational dataset and then are applied to ...
Abstract. In this paper, we propose a novel approach for adaptive control of robotic manipulators. Our approach uses a representation of inverse dynamics models learned from a vari...
We study decision making in environments where the reward is only partially observed, but can be modeled as a function of an action and an observed context. This setting, known as...
Spatial pyramid matching (SPM) is a simple yet effective approach to compute similarity between images. Similarity kernels at different regions and scales are usually fused by som...
Existing works on sentiment analysis on product reviews suffer from the following limitations: (1) The knowledge of hierarchical relationships of products attributes is not fully ...