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COLT
2008
Springer
13 years 10 months ago
Does Unlabeled Data Provably Help? Worst-case Analysis of the Sample Complexity of Semi-Supervised Learning
We study the potential benefits to classification prediction that arise from having access to unlabeled samples. We compare learning in the semi-supervised model to the standard, ...
Shai Ben-David, Tyler Lu, Dávid Pál
ACL
2006
13 years 10 months ago
Segment-Based Hidden Markov Models for Information Extraction
Hidden Markov models (HMMs) are powerful statistical models that have found successful applications in Information Extraction (IE). In current approaches to applying HMMs to IE, a...
Zhenmei Gu, Nick Cercone
TREC
2001
13 years 10 months ago
Rutgers' TREC 2001 Interactive Track Experience
Our focus this year was to investigate methods for increasing query length in interactive information searching in the Web context, and to see if these methods led to changes in t...
Nicholas J. Belkin, Colleen Cool, J. Jeng, Amymari...
ENGL
2006
84views more  ENGL 2006»
13 years 9 months ago
A framework for neural network to make business forecasting with hybrid VAR and GA components
Applying Vector Autoregression (VAR) and genetic algorithm (GA) in hybrid systems with neural network can improve the NN's prediction capability. Two case studies have been ca...
Sio Iong Ao
IJAR
2007
69views more  IJAR 2007»
13 years 8 months ago
Racing algorithms for conditional independence inference
In this article, we consider the computational aspects of deciding whether a conditional independence statement t is implied by a list of conditional independence statements L usi...
Remco R. Bouckaert, Milan Studený