Two of the most commonly used models in computational learning theory are the distribution-free model in which examples are chosen from a fixed but arbitrary distribution, and the ...
We present a new type of multi-class learning algorithm called a linear-max algorithm. Linearmax algorithms learn with a special type of attribute called a sub-expert. A sub-exper...
This paper presents a maximum entropy-based named entity recognizer (NER). It differs from previous machine learning-based NERs in that it uses information from the whole document...
In this paper we describe the difficulties inherent in making accurate, reproducible measurements of message-passing performance. We describe some of the mistakes often made in att...
The subject of this paper is a Smart Spell Checker System (SSCS) that can adapt to a particular user by using the user’s feedback for adjusting its behavior. The result of the ad...