Abstract: In this paper we present an entropy based method to analyze complex systems. Systems are treated as black boxes, which only expose information by some specified paramete...
In this paper, a supervised learning system of word sense disambiguation is presented. It is based on conditional maximum entropy models. This system acquires the linguistic knowl...
Chemical named entities represent an important facet of biomedical text. We have developed a system to use character-based ngrams, Maximum Entropy Markov Models and rescoring to r...
Predictors are inherent components of state-of-the-art microprocessors. Branch predictors are discussed actively from diverse perspectives. Performance of a branch predictor large...
Advances in computer processing power and emerging algorithms are allowing new ways of envisioning Human Computer Interaction. This paper focuses on the development of a computing...
Zhihong Zeng, Jilin Tu, Brian Pianfetti, Ming Liu,...