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MOBISYS
2008
ACM
15 years 7 months ago
MobiVMM: a virtual machine monitor for mobile phones
Mobile phones have evolved into complex systems as they have more and more new applications built-in. As a result, they are less reliable and less secure than before. Virtual Mach...
See-hwan Yoo, Yunxin Liu, Cheol-Ho Hong, Chuck Yoo...
SDM
2004
SIAM
211views Data Mining» more  SDM 2004»
15 years 6 months ago
Using Support Vector Machines for Classifying Large Sets of Multi-Represented Objects
Databases are a key technology for molecular biology which is a very data intensive discipline. Since molecular biological databases are rather heterogeneous, unification and data...
Hans-Peter Kriegel, Peer Kröger, Alexey Pryak...
IJCNN
2007
IEEE
15 years 11 months ago
Agnostic Learning versus Prior Knowledge in the Design of Kernel Machines
Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...
Gavin C. Cawley, Nicola L. C. Talbot
CLUSTER
2007
IEEE
15 years 9 months ago
Identifying energy-efficient concurrency levels using machine learning
Abstract-- Multicore microprocessors have been largely motivated by the diminishing returns in performance and the increased power consumption of single-threaded ILP microprocessor...
Matthew Curtis-Maury, Karan Singh, Sally A. McKee,...
141
Voted
TMI
2010
172views more  TMI 2010»
15 years 3 months ago
Comparison of AdaBoost and Support Vector Machines for Detecting Alzheimer's Disease Through Automated Hippocampal Segmentation
Abstract— We compared four automated methods for hippocampal segmentation using different machine learning algorithms (1) hierarchical AdaBoost, (2) Support Vector Machines (SVM)...
Jonathan H. Morra, Zhuowen Tu, Liana G. Apostolova...