Beam search is used to maintain tractability in large search spaces at the expense of completeness and optimality. We study supervised learning of linear ranking functions for con...
Similarity measures in many real applications generate indefinite similarity matrices. In this paper, we consider the problem of classification based on such indefinite similariti...
In this paper, we introduce the semantic network model (SNM), a generalization of the hidden Markov model (HMM) that uses factorization of state transition probabilities to reduce...
Stjepan Rajko, Gang Qian, Todd Ingalls, Jodi James
Although Support Vector Machines(SVM) succeed in classifying several image databases using image descriptors proposed in the literature, no single descriptor can be optimal for ge...
—Modeling data with linear combinations of a few elements from a learned dictionary has been the focus of much recent research in machine learning, neuroscience, and signal proce...