In this paper, we address the issue for learning better translation consensus in machine translation (MT) research, and explore the search of translation consensus from similar, r...
In this paper, we describe two di erent learning tasks for relational structures. When learning a classi er for structures, the relational structures in the training sets are clas...
Abstract We present a new margin-based approach to first-order rule learning. The approach addresses many of the prominent challenges in first-order rule learning, such as the comp...
In this paper, we propose a novel semi-supervised algorithm, which works under a two-view setting. Our algorithm, named Kernel Canonical Component Analysis Graph (KC-GRAPH), can e...
Abstract. This paper presents a new Bayesian approach to hyperspectral image segmentation that boosts the performance of the discriminative classifiers. This is achieved by combin...