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» A Note on Learning Vector Quantization
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TKDE
2011
332views more  TKDE 2011»
14 years 4 months ago
Adaptive Cluster Distance Bounding for High-Dimensional Indexing
—We consider approaches for similarity search in correlated, high-dimensional data-sets, which are derived within a clustering framework. We note that indexing by “vector appro...
Sharadh Ramaswamy, Kenneth Rose
74
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ICIP
2007
IEEE
15 years 3 months ago
A VQ-Based Demosaicing by Self-Similarity
In this paper, we propose a learning-based demosaicing and a restoration error detection. A Vector Quantization (VQ)based method is utilized for learning. We take advantage of a s...
Yoshikuni Nomura, Shree K. Nayar
ICTAI
2007
IEEE
15 years 3 months ago
CompoNet: Programmatically Embedding Neural Networks into AI Applications as Software Components
The provision of embedding neural networks into software applications can enable variety of Artificial Intelligence systems for individual users as well as organizations. Previous...
Uzair Ahmad, Andrey Gavrilov, Sungyoung Lee, Young...
MM
2003
ACM
84views Multimedia» more  MM 2003»
15 years 2 months ago
Temporal event clustering for digital photo collections
We present similarity-based methods to cluster digital photos by time and image content. The approach is general, unsupervised, and makes minimal assumptions regarding the structu...
Matthew L. Cooper, Jonathan Foote, Andreas Girgens...
ICONIP
2008
14 years 11 months ago
The Diversity of Regression Ensembles Combining Bagging and Random Subspace Method
Abstract. The concept of Ensemble Learning has been shown to increase predictive power over single base learners. Given the bias-variancecovariance decomposition, diversity is char...
Alexandra Scherbart, Tim W. Nattkemper