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IJAR
2010
130views more  IJAR 2010»
13 years 9 months ago
Learning locally minimax optimal Bayesian networks
We consider the problem of learning Bayesian network models in a non-informative setting, where the only available information is a set of observational data, and no background kn...
Tomi Silander, Teemu Roos, Petri Myllymäki
NIPS
2007
14 years 8 days ago
Predicting Brain States from fMRI Data: Incremental Functional Principal Component Regression
We propose a method for reconstruction of human brain states directly from functional neuroimaging data. The method extends the traditional multivariate regression analysis of dis...
Sennay Ghebreab, Arnold W. M. Smeulders, Pieter W....
APWEB
2003
Springer
14 years 2 months ago
Mining "Hidden Phrase" Definitions from the Web
Keyword searching is the most common form of document search on the Web. Many Web publishers manually annotate the META tags and titles of their pages with frequently queried phras...
Hung V. Nguyen, P. Velamuru, Deepak Kolippakkam, H...
PASTE
2010
ACM
14 years 3 months ago
Extracting compiler provenance from program binaries
We present a novel technique that identifies the source compiler of program binaries, an important element of program provenance. Program provenance answers fundamental questions...
Nathan E. Rosenblum, Barton P. Miller, Xiaojin Zhu
LREC
2010
119views Education» more  LREC 2010»
14 years 9 days ago
Predicting Morphological Types of Chinese Bi-Character Words by Machine Learning Approaches
This paper presented an overview of Chinese bi-character words' morphological types, and proposed a set of features for machine learning approaches to predict these types bas...
Ting-Hao Huang, Lun-Wei Ku, Hsin-Hsi Chen