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» Optimization on Support Vector Machines
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ICPR
2010
IEEE
15 years 1 months ago
Malware Detection on Mobile Devices Using Distributed Machine Learning
This paper presents a distributed Support Vector Machine (SVM) algorithm in order to detect malicious software (malware) on a network of mobile devices. The light-weight system mo...
Ashkan Sharifi Shamili, Christian Bauckhage, Tansu...
ICANN
2007
Springer
15 years 4 months ago
Selection of Basis Functions Guided by the L2 Soft Margin
Support Vector Machines (SVMs) for classification tasks produce sparse models by maximizing the margin. Two limitations of this technique are considered in this work: firstly, th...
Ignacio Barrio, Enrique Romero, Lluís Belan...
FCCM
1999
IEEE
111views VLSI» more  FCCM 1999»
15 years 2 months ago
Optimizing FPGA-Based Vector Product Designs
This paper presents a method, called multiple constant multiplier trees MCMTs, for producing optimized recon gurable hardware implementations of vector products. An algorithm for ...
Dan Benyamin, John D. Villasenor, Wayne Luk
ICDM
2009
IEEE
154views Data Mining» more  ICDM 2009»
14 years 7 months ago
GSML: A Unified Framework for Sparse Metric Learning
There has been significant recent interest in sparse metric learning (SML) in which we simultaneously learn both a good distance metric and a low-dimensional representation. Unfor...
Kaizhu Huang, Yiming Ying, Colin Campbell
AI
2011
Springer
14 years 1 months ago
Using a Heterogeneous Dataset for Emotion Analysis in Text
In this paper, we adopt a supervised machine learning approach to recognize six basic emotions (anger, disgust, fear, happiness, sadness and surprise) using a heterogeneous emotion...
Soumaya Chaffar, Diana Inkpen