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ICML
2006
IEEE
14 years 10 months ago
Accelerated training of conditional random fields with stochastic gradient methods
We apply Stochastic Meta-Descent (SMD), a stochastic gradient optimization method with gain vector adaptation, to the training of Conditional Random Fields (CRFs). On several larg...
S. V. N. Vishwanathan, Nicol N. Schraudolph, Mark ...
KDD
2004
ACM
330views Data Mining» more  KDD 2004»
14 years 9 months ago
Learning to detect malicious executables in the wild
In this paper, we describe the development of a fielded application for detecting malicious executables in the wild. We gathered 1971 benign and 1651 malicious executables and enc...
Jeremy Z. Kolter, Marcus A. Maloof
CVPR
2006
IEEE
14 years 11 months ago
Incorporating the Boltzmann Prior in Object Detection Using SVM
In this paper we discuss object detection when only a small number of training examples are given. Specifically, we show how to incorporate a simple prior on the distribution of n...
Margarita Osadchy, Daniel Keren
BMCBI
2008
88views more  BMCBI 2008»
13 years 9 months ago
Use of machine learning algorithms to classify binary protein sequences as highly-designable or poorly-designable
Background: By using a standard Support Vector Machine (SVM) with a Sequential Minimal Optimization (SMO) method of training, Na
Myron Peto, Andrzej Kloczkowski, Vasant Honavar, R...
PAMI
2011
13 years 4 months ago
Revisiting Linear Discriminant Techniques in Gender Recognition
—Emerging applications of computer vision and pattern recognition in mobile devices and networked computing require the development of resourcelimited algorithms. Linear classifi...
Juan Bekios-Calfa, José Miguel Buenaposada,...