In recent years analysis of complexity of learning Gaussian mixture models from sampled data has received significant attention in computational machine learning and theory commun...
Inductive learning of first-order theory based on examples has serious bottleneck in the enormous hypothesis search space needed, making existing learning approaches perform poorl...
A key challenge in applying kernel-based methods for discriminative learning is to identify a suitable kernel given a problem domain. Many methods instead transform the input data...
One of the difficulties in second language (L2) learning is the weakness in discriminating between acoustic diversity within an L2 phoneme category and between different categori...
This paper proposes a method for automatic maintaining the similarity information for a particular class of Flexible Query Answering Systems (FQAS). The paper describes the three m...