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» Information Theory, Inference, and Learning Algorithms
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NIPS
2008
13 years 9 months ago
One sketch for all: Theory and Application of Conditional Random Sampling
Conditional Random Sampling (CRS) was originally proposed for efficiently computing pairwise (l2, l1) distances, in static, large-scale, and sparse data. This study modifies the o...
Ping Li, Kenneth Ward Church, Trevor Hastie
AVSS
2009
IEEE
14 years 2 months ago
Event Composition with Imperfect Information for Bus Surveillance
—Demand for bus surveillance is growing due to the increased threats of terrorist attack, vandalism and litigation. However, CCTV systems are traditionally used in forensic mode,...
Jianbing Ma, Weiru Liu, Paul Miller, Weiqi Yan
APN
2010
Springer
13 years 6 months ago
Learning Workflow Petri Nets
Workflow mining is the task of automatically producing a workflow model from a set of event logs recording sequences of workflow events; each sequence corresponds to a use case or ...
Javier Esparza, Martin Leucker, Maximilian Schlund
ICML
2007
IEEE
14 years 8 months ago
The matrix stick-breaking process for flexible multi-task learning
In multi-task learning our goal is to design regression or classification models for each of the tasks and appropriately share information between tasks. A Dirichlet process (DP) ...
Ya Xue, David B. Dunson, Lawrence Carin
IEEECIT
2010
IEEE
13 years 5 months ago
Learning Autonomic Security Reconfiguration Policies
Abstract--We explore the idea of applying machine learning techniques to automatically infer risk-adaptive policies to reconfigure a network security architecture when the context ...
Juan E. Tapiador, John A. Clark