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FOCS
1990
IEEE
15 years 1 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
15 years 10 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
14 years 9 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
15 years 1 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
15 years 2 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