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» Graph Structure Learning for Task Ordering
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SIBGRAPI
2008
IEEE
14 years 1 months ago
Structural Matching of 2D Electrophoresis Gels using Graph Models
2D electrophoresis is a well known method for protein separation which is extremely useful in the field of proteomics. Each spot in the image represents a protein accumulation an...
Alexandre Noma, Alvaro Pardo, Roberto Marcondes Ce...
ICML
2005
IEEE
14 years 7 months ago
Combining model-based and instance-based learning for first order regression
T ORDER REGRESSION (EXTENDED ABSTRACT) Kurt Driessensa Saso Dzeroskib a Department of Computer Science, University of Waikato, Hamilton, New Zealand (kurtd@waikato.ac.nz) b Departm...
Kurt Driessens, Saso Dzeroski
KDD
2009
ACM
172views Data Mining» more  KDD 2009»
13 years 11 months ago
Learning dynamic temporal graphs for oil-production equipment monitoring system
Learning temporal graph structures from time series data reveals important dependency relationships between current observations and histories. Most previous work focuses on learn...
Yan Liu, Jayant R. Kalagnanam, Oivind Johnsen
ICPR
2008
IEEE
14 years 8 months ago
Supervised learning of a generative model for edge-weighted graphs
This paper addresses the problem of learning archetypal structural models from examples. To this end we define a generative model for graphs where the distribution of observed nod...
Andrea Torsello, David L. Dowe
IMCSIT
2010
13 years 4 months ago
German subordinate clause word order in dialogue-based CALL.
We present a dialogue system for exercising the German subordinate clause word order. The pedagogical methodology we adopt is based on focused tasks: the targeted linguistic struct...
Magdalena Wolska, Sabrina Wilske