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ILP
2001
Springer
15 years 7 months ago
Learning Functions from Imperfect Positive Data
The Bayesian framework of learning from positive noise-free examples derived by Muggleton [12] is extended to learning functional hypotheses from positive examples containing norma...
Filip Zelezný
133
Voted
EMNLP
2010
15 years 19 days ago
Improved Fully Unsupervised Parsing with Zoomed Learning
We introduce a novel training algorithm for unsupervised grammar induction, called Zoomed Learning. Given a training set T and a test set S, the goal of our algorithm is to identi...
Roi Reichart, Ari Rappoport
127
Voted
IJAR
2010
152views more  IJAR 2010»
15 years 1 months ago
Structural-EM for learning PDG models from incomplete data
Probabilistic Decision Graphs (PDGs) are a class of graphical models that can naturally encode some context specific independencies that cannot always be efficiently captured by...
Jens D. Nielsen, Rafael Rumí, Antonio Salme...
165
Voted
AAAI
2010
15 years 4 months ago
Unsupervised Learning of Event Classes from Video
We present a method for unsupervised learning of event classes from videos in which multiple actions might occur simultaneously. It is assumed that all such activities are produce...
Muralikrishna Sridhar, Anthony G. Cohn, David C. H...
110
Voted
AGILEDC
2007
IEEE
15 years 9 months ago
Growing a Build Management System from Seed
This paper describes the authors’ experiences creating a full Build Management System from a simple Version Control System. We will explore how the XP values of simplicity, feed...
Narti Kitiyakara, Joseph Graves