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» Metric and Kernel Learning Using a Linear Transformation
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ICCAD
2004
IEEE
83views Hardware» more  ICCAD 2004»
15 years 10 months ago
Custom-optimized multiplierless implementations of DSP algorithms
Linear DSP kernels such as transforms and filters are comprised exclusively of additions and multiplications by constants. These multiplications may be realized as networks of ad...
Markus Püschel, Adam C. Zelinski, James C. Ho...
ESANN
2007
15 years 3 months ago
Interval discriminant analysis using support vector machines
Imprecision, incompleteness, prior knowledge or improved learning speed can motivate interval–represented data. Most approaches for SVM learning of interval data use local kernel...
Cecilio Angulo, Davide Anguita, Luis Gonzál...
ICCV
2005
IEEE
16 years 3 months ago
The Pyramid Match Kernel: Discriminative Classification with Sets of Image Features
Discriminative learning is challenging when examples are sets of features, and the sets vary in cardinality and lack any sort of meaningful ordering. Kernel-based classification m...
Kristen Grauman, Trevor Darrell
CVPR
2004
IEEE
15 years 5 months ago
Learning in Region-Based Image Retrieval with Generalized Support Vector Machines
Relevance feedback approaches based on support vector machine (SVM) learning have been applied to significantly improve retrieval performance in content-based image retrieval (CBI...
Iker Gondra, Douglas R. Heisterkamp
139
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ECCV
2010
Springer
15 years 3 months ago
Improving the Fisher Kernel for Large-Scale Image Classification
Abstract. The Fisher kernel (FK) is a generic framework which combines the benefits of generative and discriminative approaches. In the context of image classification the FK was s...