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IJSI
2008
156views more  IJSI 2008»
13 years 7 months ago
Co-Training by Committee: A Generalized Framework for Semi-Supervised Learning with Committees
Many data mining applications have a large amount of data but labeling data is often difficult, expensive, or time consuming, as it requires human experts for annotation. Semi-supe...
Mohamed Farouk Abdel Hady, Friedhelm Schwenker
JACM
2000
131views more  JACM 2000»
13 years 7 months ago
The soft heap: an approximate priority queue with optimal error rate
A simple variant of a priority queue, called a soft heap, is introduced. The data structure supports the usual operations: insert, delete, meld, and findmin. Its novelty is to beat...
Bernard Chazelle
NIPS
2003
13 years 9 months ago
Unsupervised Context Sensitive Language Acquisition from a Large Corpus
We describe a pattern acquisition algorithm that learns, in an unsupervised fashion, a streamlined representation of linguistic structures from a plain natural-language corpus. Th...
Zach Solan, David Horn, Eytan Ruppin, Shimon Edelm...
COLING
2002
13 years 7 months ago
Learning Verb Argument Structure from Minimally Annotated Corpora
In this paper we investigate the task of automatically identifying the correct argument structure for a set of verbs. The argument structure of a verb allows us to predict the rel...
Anoop Sarkar, Woottiporn Tripasai
STACS
1992
Springer
13 years 11 months ago
Speeding Up Two String-Matching Algorithms
We show how to speed up two string-matching algorithms: the Boyer-Moore algorithm (BM algorithm), and its version called here the reverse factor algorithm (RF algorithm). The RF al...
Maxime Crochemore, Thierry Lecroq, Artur Czumaj, L...