In streamwise feature selection, new features are sequentially considered for addition to a predictive model. When the space of potential features is large, streamwise feature sel...
Jing Zhou, Dean P. Foster, Robert A. Stine, Lyle H...
Many complex, real world phenomena are difficult to study directly using controlled experiments. Instead, the use of computer simulations has become commonplace as a feasible alte...
The Hierarchical Hidden Markov Model (HHMM) is a well formalized tool suitable to model complex patterns in long temporal or spatial sequences. Even if effective algorithms are ava...
Forest resource management systems and forest landscape visualization applications often need usersteered interactive displays of a forest landscape representing the underlying fo...
Qizhi Yu, Chongcheng Chen, Zhigeng Pan, Tianhe Chi
This paper describes a top-down word image generation model for holistic handwritten word recognition. To generate a word image, it uses likelihoods based, respectively, on a ling...