We address the learning of trust based on past observations and context information. We argue that from the truster's point of view trust is best expressed as one of several ...
A novel random text generation model is introduced. Unlike in previous random text models, that mainly aim at producing a Zipfian distribution of word frequencies, our model also ...
A physical yet compact gate delay model is developed integrating short-channel effects and the Alpha-power law based timing model. This analytical approach accurately predicts bot...
We propose new methods to exploit contemporaneous text, such as on-line news articles, to improve language models for automatic speech recognition and other natural language proce...
We desert'be our latest attempt at adaptive language modeling. At the heart of our approachis a Maximum Entropy(ME) modelwhich inc.orlxnatesmanyknowledgesources in a consiste...