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» Algorithmic randomness of continuous functions
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APPROX
2008
Springer
101views Algorithms» more  APPROX 2008»
14 years 1 months ago
Learning Random Monotone DNF
We give an algorithm that with high probability properly learns random monotone DNF with t(n) terms of length log t(n) under the uniform distribution on the Boolean cube {0, 1}n ....
Jeffrey C. Jackson, Homin K. Lee, Rocco A. Servedi...
GECCO
2010
Springer
180views Optimization» more  GECCO 2010»
14 years 3 months ago
Comparing results of 31 algorithms from the black-box optimization benchmarking BBOB-2009
This paper presents results of the BBOB-2009 benchmarking of 31 search algorithms on 24 noiseless functions in a black-box optimization scenario in continuous domain. The runtime ...
Nikolaus Hansen, Anne Auger, Raymond Ros, Steffen ...
PAMI
2006
440views more  PAMI 2006»
13 years 11 months ago
Random Walks for Image Segmentation
Abstract-- A novel method is proposed for performing multilabel, interactive image segmentation. Given a small number of pixels with user-defined (or pre-defined) labels, one can a...
Leo Grady
ASPDAC
2009
ACM
164views Hardware» more  ASPDAC 2009»
14 years 5 months ago
Accounting for non-linear dependence using function driven component analysis
Majority of practical multivariate statistical analyses and optimizations model interdependence among random variables in terms of the linear correlation among them. Though linear...
Lerong Cheng, Puneet Gupta, Lei He
ECML
2007
Springer
14 years 2 months ago
Efficient Continuous-Time Reinforcement Learning with Adaptive State Graphs
Abstract. We present a new reinforcement learning approach for deterministic continuous control problems in environments with unknown, arbitrary reward functions. The difficulty of...
Gerhard Neumann, Michael Pfeiffer, Wolfgang Maass