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FOCS
1990
IEEE
13 years 11 months ago
Separating Distribution-Free and Mistake-Bound Learning Models over the Boolean Domain
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 ...
Avrim Blum
ICML
2003
IEEE
14 years 7 months ago
Using Linear-threshold Algorithms to Combine Multi-class Sub-experts
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...
Chris Mesterharm
COLING
2002
13 years 6 months ago
Named Entity Recognition: A Maximum Entropy Approach Using Global Information
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...
Hai Leong Chieu, Hwee Tou Ng
PVM
1999
Springer
13 years 11 months ago
Reproducible Measurements of MPI Performance Characteristics
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...
William Gropp, Ewing L. Lusk
IWSAS
2001
Springer
13 years 11 months ago
SSCS: A Smart Spell Checker System Implementation Using Adaptive Software Architecture
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...
Deepak Seth, Mieczyslaw M. Kokar