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ESANN
2004
13 years 9 months ago
Neural methods for non-standard data
Standard pattern recognition provides effective and noise-tolerant tools for machine learning tasks; however, most approaches only deal with real vectors of a finite and fixed dime...
Barbara Hammer, Brijnesh J. Jain
SDM
2009
SIAM
161views Data Mining» more  SDM 2009»
14 years 4 months ago
Feature Weighted SVMs Using Receiver Operating Characteristics.
Support Vector Machines (SVMs) are a leading tool in classification and pattern recognition and the kernel function is one of its most important components. This function is used...
Shaoyi Zhang, M. Maruf Hossain, Md. Rafiul Hassan,...
IBPRIA
2007
Springer
14 years 1 months ago
Parsimonious Kernel Fisher Discrimination
Abstract. By applying recent results in optimization transfer, a new algorithm for kernel Fisher Discriminant Analysis is provided that makes use of a non-smooth penalty on the coe...
Kitsuchart Pasupa, Robert F. Harrison, Peter Wille...
PCM
2010
Springer
223views Multimedia» more  PCM 2010»
13 years 6 months ago
Discovering Motion Patterns for Human Action Recognition
In this paper, we propose a novel Spatiotemporal Interest Point (MC-STIP) detector based on the coherent motion pattern around each voxel in videos. Our detector defines the local...
Ziming Zhang, Jiawei Huang, Ze-Nian Li
SSPR
2010
Springer
13 years 5 months ago
Information Theoretical Kernels for Generative Embeddings Based on Hidden Markov Models
Many approaches to learning classifiers for structured objects (e.g., shapes) use generative models in a Bayesian framework. However, state-of-the-art classifiers for vectorial d...
André F. T. Martins, Manuele Bicego, Vittor...