In this paper, we investigate a simple, mistakedriven learning algorithm for discriminative training of continuous density hidden Markov models (CD-HMMs). Most CD-HMMs for automat...
Hierarchies are an intuitive and effective organization paradigm for data. Of late there has been considerable research on automatically learning hierarchical organizations of dat...
Background: It is a major challenge of computational biology to provide a comprehensive functional classification of all known proteins. Most existing methods seek recurrent patte...
Clock networks contribute a significant fraction of dynamic power and can be a limiting factor in high-performance CPUs and SoCs. The need for multi-objective optimization over a l...
We will demonstrate our system, called V iStream, supporting interactive visual exploration of neighbor-based patterns [7] in data streams. V istream does not only apply innovativ...
Di Yang, Zhenyu Guo, Zaixian Xie, Elke A. Rundenst...