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» Finding nuggets in documents: A machine learning approach
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ICML
2010
IEEE
13 years 10 months ago
Learning Markov Logic Networks Using Structural Motifs
Markov logic networks (MLNs) use firstorder formulas to define features of Markov networks. Current MLN structure learners can only learn short clauses (4-5 literals) due to extre...
Stanley Kok, Pedro Domingos
AI
1999
Springer
13 years 8 months ago
Learning by Discovering Concept Hierarchies
We present a new machine learning method that, given a set of training examples, induces a definition of the target concept in terms of a hierarchy of intermediate concepts and th...
Blaz Zupan, Marko Bohanec, Janez Demsar, Ivan Brat...
ICML
2006
IEEE
14 years 9 months ago
Efficient MAP approximation for dense energy functions
We present an efficient method for maximizing energy functions with first and second order potentials, suitable for MAP labeling estimation problems that arise in undirected graph...
Marius Leordeanu, Martial Hebert
ICML
2005
IEEE
14 years 9 months ago
Near-optimal sensor placements in Gaussian processes
When monitoring spatial phenomena, which are often modeled as Gaussian Processes (GPs), choosing sensor locations is a fundamental task. A common strategy is to place sensors at t...
Carlos Guestrin, Andreas Krause, Ajit Paul Singh
ECIR
1998
Springer
13 years 10 months ago
Coupled Hierarchical IR and Stochastic Models for Surface Information Extraction
We present in this paper a combination of Machine Learning based Information Retrieval (IR) techniques and stochastic language modelling in a hierarchical system that extracts sur...
Hugo Zaragoza, Patrick Gallinari