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CCS
2006
ACM
15 years 1 months ago
Can machine learning be secure?
Machine learning systems offer unparalled flexibility in dealing with evolving input in a variety of applications, such as intrusion detection systems and spam e-mail filtering. H...
Marco Barreno, Blaine Nelson, Russell Sears, Antho...
ATAL
2007
Springer
15 years 3 months ago
A framework for agent-based distributed machine learning and data mining
This paper proposes a framework for agent-based distributed machine learning and data mining based on (i) the exchange of meta-level descriptions of individual learning processes ...
Jan Tozicka, Michael Rovatsos, Michal Pechoucek
CCR
2006
114views more  CCR 2006»
14 years 9 months ago
A preliminary performance comparison of five machine learning algorithms for practical IP traffic flow classification
The identification of network applications through observation of associated packet traffic flows is vital to the areas of network management and surveillance. Currently popular m...
Nigel Williams, Sebastian Zander, Grenville J. Arm...
EMNLP
2009
14 years 7 months ago
On the Use of Virtual Evidence in Conditional Random Fields
Virtual evidence (VE), first introduced by (Pearl, 1988), provides a convenient way of incorporating prior knowledge into Bayesian networks. This work generalizes the use of VE to...
Xiao Li
95
Voted
NSDI
2007
14 years 12 months ago
Black-box and Gray-box Strategies for Virtual Machine Migration
Virtualization can provide significant benefits in data centers by enabling virtual machine migration to eliminate hotspots. We present Sandpiper, a system that automates the ta...
Timothy Wood, Prashant J. Shenoy, Arun Venkatarama...