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ICML
2005
IEEE
14 years 9 months ago
Building Sparse Large Margin Classifiers
This paper presents an approach to build Sparse Large Margin Classifiers (SLMC) by adding one more constraint to the standard Support Vector Machine (SVM) training problem. The ad...
Bernhard Schölkopf, Gökhan H. Bakir, Min...
MICRO
2005
IEEE
130views Hardware» more  MICRO 2005»
14 years 1 months ago
Exploiting Vector Parallelism in Software Pipelined Loops
An emerging trend in processor design is the addition of short vector instructions to general-purpose and embedded ISAs. Frequently, these extensions are employed using traditiona...
Samuel Larsen, Rodric M. Rabbah, Saman P. Amarasin...
ICONIP
2008
13 years 9 months ago
An Evaluation of Machine Learning-Based Methods for Detection of Phishing Sites
In this paper, we present the performance of machine learning-based methods for detection of phishing sites. We employ 9 machine learning techniques including AdaBoost, Bagging, S...
Daisuke Miyamoto, Hiroaki Hazeyama, Youki Kadobaya...
ICAC
2006
IEEE
14 years 2 months ago
Fast and Effective Worm Fingerprinting via Machine Learning
— As Internet worms become ever faster and more sophisticated, it is important to be able to extract worm signatures in an accurate and timely manner. In this paper, we apply mac...
Stewart M. Yang, Jianping Song, Harish Rajamani, T...
AAAI
2006
13 years 9 months ago
A Simple and Effective Method for Incorporating Advice into Kernel Methods
We propose a simple mechanism for incorporating advice (prior knowledge), in the form of simple rules, into support-vector methods for both classification and regression. Our appr...
Richard Maclin, Jude W. Shavlik, Trevor Walker, Li...