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ICML
2002
IEEE
16 years 7 months ago
Learning the Kernel Matrix with Semi-Definite Programming
Kernel-based learning algorithms work by embedding the data into a Euclidean space, and then searching for linear relations among the embedded data points. The embedding is perfor...
Gert R. G. Lanckriet, Nello Cristianini, Peter L. ...
KDD
2006
ACM
179views Data Mining» more  KDD 2006»
16 years 7 months ago
Extracting key-substring-group features for text classification
In many text classification applications, it is appealing to take every document as a string of characters rather than a bag of words. Previous research studies in this area mostl...
Dell Zhang, Wee Sun Lee
ALT
2006
Springer
16 years 3 months ago
Learning Linearly Separable Languages
This paper presents a novel paradigm for learning languages that consists of mapping strings to an appropriate high-dimensional feature space and learning a separating hyperplane i...
Leonid Kontorovich, Corinna Cortes, Mehryar Mohri
SOSP
2009
ACM
16 years 3 months ago
The multikernel: a new OS architecture for scalable multicore systems
Commodity computer systems contain more and more processor cores and exhibit increasingly diverse architectural tradeoffs, including memory hierarchies, interconnects, instructio...
Andrew Baumann, Paul Barham, Pierre-Évarist...
ACSAC
2009
IEEE
16 years 1 months ago
MAVMM: Lightweight and Purpose Built VMM for Malware Analysis
—Malicious software is rampant on the Internet and costs billions of dollars each year. Safe and thorough analysis of malware is key to protecting vulnerable systems and cleaning...
Anh M. Nguyen, Nabil Schear, HeeDong Jung, Apeksha...