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ICML
2000
IEEE
16 years 5 months ago
Learning Subjective Functions with Large Margins
In manyoptimization and decision problems the objective function can be expressed as a linear combinationof competingcriteria, the weights of whichspecify the relative importanceo...
Claude-Nicolas Fiechter, Seth Rogers
ICAC
2005
IEEE
15 years 10 months ago
PICCIL: Interactive Learning to Support Log File Categorization
Motivated by the real-world application of categorizing system log messages into defined situation categories, this paper describes an interactive text categorization method, PICC...
David Loewenstern, Sheng Ma, Abdi Salahshour
MT
2002
118views more  MT 2002»
15 years 4 months ago
MT for Minority Languages Using Elicitation-Based Learning of Syntactic Transfer Rules
The AVENUE project contains a run-time machine translation program that is surrounded by pre- and post-run-time modules. The post-run-time module selects among translation alternat...
Katharina Probst, Lori S. Levin, Erik Peterson, Al...
KDD
2009
ACM
172views Data Mining» more  KDD 2009»
15 years 9 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
ESANN
2006
15 years 5 months ago
Learning Visual Invariance
Invariance is a necessary feature of a visual system able to recognize real objects in all their possible appearance. It is also the processing step most problematic to understand ...
Alessio Plebe