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AUSAI
2008
Springer
14 years 11 months ago
Learning Object Representations Using Sequential Patterns
This paper explores the use of alternating sequential patterns of local features and saccading actions to learn robust and compact object representations. The temporal encoding rep...
Nobuyuki Morioka
KDD
2009
ACM
269views Data Mining» more  KDD 2009»
15 years 10 months ago
Extracting discriminative concepts for domain adaptation in text mining
One common predictive modeling challenge occurs in text mining problems is that the training data and the operational (testing) data are drawn from different underlying distributi...
Bo Chen, Wai Lam, Ivor Tsang, Tak-Lam Wong
PR
2007
148views more  PR 2007»
14 years 9 months ago
Learning the best subset of local features for face recognition
We propose a novel, local feature-based face representation method based on twostage subset selection where the first stage finds the informative regions and the second stage ...
Berk Gökberk, M. Okan Irfanoglu, Lale Akarun,...
JMLR
2010
119views more  JMLR 2010»
14 years 4 months ago
Semi-Supervised Learning via Generalized Maximum Entropy
Various supervised inference methods can be analyzed as convex duals of the generalized maximum entropy (MaxEnt) framework. Generalized MaxEnt aims to find a distribution that max...
Ayse Erkan, Yasemin Altun
ICCV
2005
IEEE
15 years 11 months ago
Efficient Learning of Relational Object Class Models
We present an efficient method for learning part-based object class models from unsegmented images represented as sets of salient features. A model includes parts' appearance...
Aharon Bar-Hillel, Tomer Hertz, Daphna Weinshall