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» Algorithm Selection using Reinforcement Learning
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ML
2010
ACM
163views Machine Learning» more  ML 2010»
14 years 9 months ago
Classification with guaranteed probability of error
We introduce a general-purpose learning machine that we call the Guaranteed Error Machine, or GEM, and two learning algorithms, a real GEM algorithm and an ideal GEM algorithm. Th...
Marco C. Campi
GECCO
2008
Springer
206views Optimization» more  GECCO 2008»
15 years 3 months ago
Improving accuracy of immune-inspired malware detectors by using intelligent features
In this paper, we show that a Bio-inspired classifier’s accuracy can be dramatically improved if it operates on intelligent features. We propose a novel set of intelligent feat...
M. Zubair Shafiq, Syed Ali Khayam, Muddassar Faroo...
CCS
2010
ACM
15 years 2 months ago
Demonstrating cognitive packet network resilience to worm attacks
The need for network stability and reliability has led to the growth of autonomic networks [2] that can provide more stable and more reliable communications via on-line measuremen...
Georgia Sakellari, Erol Gelenbe
FOIKS
2008
Springer
15 years 11 months ago
Cost-minimising strategies for data labelling : optimal stopping and active learning
Supervised learning deals with the inference of a distribution over an output or label space $\CY$ conditioned on points in an observation space $\CX$, given a training dataset $D$...
Christos Dimitrakakis, Christian Savu-Krohn
ICCV
2005
IEEE
15 years 7 months ago
Contour-Based Learning for Object Detection
We present a novel categorical object detection scheme that uses only local contour-based features. A two-stage, partially supervised learning architecture is proposed: a rudiment...
Jamie Shotton, Andrew Blake, Roberto Cipolla