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KDD
2005
ACM
117views Data Mining» more  KDD 2005»
14 years 9 months ago
Rule extraction from linear support vector machines
We describe an algorithm for converting linear support vector machines and any other arbitrary hyperplane-based linear classifiers into a set of non-overlapping rules that, unlike...
Glenn Fung, Sathyakama Sandilya, R. Bharat Rao
ICCD
2005
IEEE
246views Hardware» more  ICCD 2005»
14 years 6 months ago
H-SIMD Machine: Configurable Parallel Computing for Matrix Multiplication
FPGAs (Field-Programmable Gate Arrays) are often used as coprocessors to boost the performance of dataintensive applications [1, 2]. However, mapping algorithms onto multimillion-...
Xizhen Xu, Sotirios G. Ziavras
ICMCS
2005
IEEE
229views Multimedia» more  ICMCS 2005»
14 years 2 months ago
A methodology for improving recognition rate of linear discriminant analysis in video-based face recognition using support vecto
This paper proposes a two-step methodology for improving the discriminatory power of Linear Discriminant Analysis (LDA) for video-based human face recognition. Results indicate th...
Sreekar Krishna, Sethuraman Panchanathan
ICCV
2007
IEEE
13 years 11 months ago
Combined Support Vector Machines and Hidden Markov Models for Modeling Facial Action Temporal Dynamics
The analysis of facial expression temporal dynamics is of great importance for many real-world applications. Being able to automatically analyse facial muscle actions (Action Units...
Michel François Valstar, Maja Pantic
NIPS
2004
13 years 10 months ago
A Topographic Support Vector Machine: Classification Using Local Label Configurations
The standard approach to the classification of objects is to consider the examples as independent and identically distributed (iid). In many real world settings, however, this ass...
Johannes Mohr, Klaus Obermayer