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KDD
2008
ACM
150views Data Mining» more  KDD 2008»
14 years 8 months ago
Hypergraph spectral learning for multi-label classification
A hypergraph is a generalization of the traditional graph in which the edges are arbitrary non-empty subsets of the vertex set. It has been applied successfully to capture highord...
Liang Sun, Shuiwang Ji, Jieping Ye
PAMI
2012
11 years 10 months ago
Trainable Convolution Filters and Their Application to Face Recognition
—In this paper, we present a novel image classification system that is built around a core of trainable filter ensembles that we call Volterra kernel classifiers. Our system trea...
Ritwik Kumar, Arunava Banerjee, Baba C. Vemuri, Ha...
MICCAI
2010
Springer
13 years 6 months ago
Generalized Sparse Classifiers for Decoding Cognitive States in fMRI
The high dimensionality of functional magnetic resonance imaging (fMRI) data presents major challenges to fMRI pattern classification. Directly applying standard classifiers often ...
Bernard Ng, Arash Vahdat, Ghassan Hamarneh, Rafeef...
MICCAI
2003
Springer
14 years 8 months ago
Freehand Ultrasound Reconstruction Based on ROI Prior Modeling and Normalized Convolution
3D freehand ultrasound imaging is becoming a widespread technique in medical examinations. This imaging technique produces a set of irregularly spaced B-scans. Reconstructing a reg...
Raúl San José Estépar, Marcos...
KDD
2008
ACM
259views Data Mining» more  KDD 2008»
14 years 8 months ago
Using ghost edges for classification in sparsely labeled networks
We address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. Techniques for statistical re...
Brian Gallagher, Hanghang Tong, Tina Eliassi-Rad, ...