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CVPR
2006
IEEE
14 years 9 months ago
Dimensionality Reduction by Learning an Invariant Mapping
Dimensionality reduction involves mapping a set of high dimensional input points onto a low dimensional manifold so that "similar" points in input space are mapped to ne...
Raia Hadsell, Sumit Chopra, Yann LeCun
CHI
1999
ACM
13 years 12 months ago
Learning and Performing by Exploration: Label Quality Measured by Latent Semantic Analysis
Models of learning and performing by exploration assume that the semantic distance between task descriptions and screen labels controls in part the usersÕ search strategies. Neve...
Rodolfo Soto
ICDM
2009
IEEE
137views Data Mining» more  ICDM 2009»
14 years 2 months ago
Regression Learning Vector Quantization
— Learning Vector Quantization (LVQ) is a popular class of nearest prototype classifiers for multiclass classification. Learning algorithms from this family are widely used becau...
Mihajlo Grbovic, Slobodan Vucetic
NIPS
2004
13 years 9 months ago
Multiple Relational Embedding
We describe a way of using multiple different types of similarity relationship to learn a low-dimensional embedding of a dataset. Our method chooses different, possibly overlappin...
Roland Memisevic, Geoffrey E. Hinton
IVC
2007
176views more  IVC 2007»
13 years 7 months ago
Kernel-based distance metric learning for content-based image retrieval
ct 8 For a specific set of features chosen for representing images, the performance of a content-based image retrieval (CBIR) system 9 depends critically on the similarity or diss...
Hong Chang, Dit-Yan Yeung