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CVPR
2006
IEEE
15 years 1 days ago
Learning Object Shape: From Drawings to Images
We consider the important challenge of recognizing a variety of deformable object classes in images. Of fundamental importance and particular difficulty in this setting is the pro...
Gal Elidan, Geremy Heitz, Daphne Koller
ICTAI
2009
IEEE
14 years 4 months ago
Probabilistic Neural Logic Network Learning: Taking Cues from Neuro-Cognitive Processes
This paper describes an attempt to devise a knowledge discovery model that is inspired from the two theoretical frameworks of selectionism and constructivism in human cognitive le...
Henry Wai Kit Chia, Chew Lim Tan, Sam Yuan Sung
FUZZIEEE
2007
IEEE
14 years 4 months ago
Learning Fuzzy Linguistic Models from Low Quality Data by Genetic Algorithms
— Incremental rule base learning techniques can be used to learn models and classifiers from interval or fuzzyvalued data. These algorithms are efficient when the observation e...
Luciano Sánchez, José Otero
TACAS
2007
Springer
117views Algorithms» more  TACAS 2007»
14 years 4 months ago
Replaying Play In and Play Out: Synthesis of Design Models from Scenarios by Learning
This paper is concerned with bridging the gap between requirements, provided as a set of scenarios, and conforming design models. The novel aspect of our approach is to exploit lea...
Benedikt Bollig, Joost-Pieter Katoen, Carsten Kern...
ICASSP
2010
IEEE
13 years 10 months ago
Learning from high-dimensional noisy data via projections onto multi-dimensional ellipsoids
In this paper, we examine the problem of learning from noisecontaminated data in high-dimensional space. A new learning approach based on projections onto multi-dimensional ellips...
Liuling Gong, Dan Schonfeld