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TNN
1998
146views more  TNN 1998»
15 years 2 months ago
Fuzzy lattice neural network (FLNN): a hybrid model for learning
— This paper proposes two hierarchical schemes for learning, one for clustering and the other for classification problems. Both schemes can be implemented on a fuzzy lattice neu...
Vassilios Petridis, Vassilis G. Kaburlasos
ICCV
2009
IEEE
15 years 27 days ago
Learning with dynamic group sparsity
This paper investigates a new learning formulation called dynamic group sparsity. It is a natural extension of the standard sparsity concept in compressive sensing, and is motivat...
Junzhou Huang, Xiaolei Huang, Dimitris N. Metaxas
JMLR
2010
113views more  JMLR 2010»
14 years 10 months ago
Optimal Search on Clustered Structural Constraint for Learning Bayesian Network Structure
We study the problem of learning an optimal Bayesian network in a constrained search space; skeletons are compelled to be subgraphs of a given undirected graph called the super-st...
Kaname Kojima, Eric Perrier, Seiya Imoto, Satoru M...
ECCV
2006
Springer
16 years 5 months ago
Learning Discriminative Canonical Correlations for Object Recognition with Image Sets
Abstract. We address the problem of comparing sets of images for object recognition, where the sets may represent arbitrary variations in an object's appearance due to changin...
Tae-Kyun Kim, Josef Kittler, Roberto Cipolla
237
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ICDE
2000
IEEE
189views Database» more  ICDE 2000»
16 years 4 months ago
Image Database Retrieval with Multiple-Instance Learning Techniques
In this paper, we develop and test an approach to retrieving images from an image database based on content similarity. First, each picture is divided into many overlapping region...
Cheng Yang, Tomás Lozano-Pérez