This paper presents a neural network approach to the problem of nding the dialogue act for a given utterance. So far only symbolic, decision tree and statistical approaches were ut...
This paper introduces new methods based on exponential families for modeling the correlations between words in text and speech. While previous work assumed the effects of word co-...
High throughput glycoproteomics, similar to genomics and proteomics, involves extremely large volumes of distributed, heterogeneous data as a basis for identification and quantifi...
Satya Sanket Sahoo, Christopher Thomas, Amit P. Sh...
This paper describes a novel application of Statistical Learning Theory (SLT) to control model complexity in flow estimation. SLT provides analytical generalization bounds suitabl...
Zoran Duric, Fayin Li, Harry Wechsler, Vladimir Ch...
Abstract--To achieve a high product quality for nano-scale systems both realistic defect mechanisms and process variations must be taken into account. While existing approaches for...