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» UMDAs for dynamic optimization problems
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ICCV
2005
IEEE
15 years 6 months ago
KALMANSAC: Robust Filtering by Consensus
We propose an algorithm to perform causal inference of the state of a dynamical model when the measurements are corrupted by outliers. While the optimal (maximumlikelihood) soluti...
Andrea Vedaldi, Hailin Jin, Paolo Favaro, Stefano ...
114
Voted
GECCO
2010
Springer
191views Optimization» more  GECCO 2010»
15 years 29 days ago
Fitness importance for online evolution
To complement standard fitness functions, we propose "Fitness Importance" (FI) as a novel meta-heuristic for online learning systems. We define FI and show how it can be...
Philip Valencia, Raja Jurdak, Peter Lindsay
104
Voted
JMLR
2008
92views more  JMLR 2008»
15 years 22 days ago
Theoretical Advantages of Lenient Learners: An Evolutionary Game Theoretic Perspective
This paper presents the dynamics of multiple learning agents from an evolutionary game theoretic perspective. We provide replicator dynamics models for cooperative coevolutionary ...
Liviu Panait, Karl Tuyls, Sean Luke
190
Voted
POPL
2003
ACM
16 years 1 months ago
New results on the computability and complexity of points - to analysis
Given a program and two variables p and q, the goal of points-to analysis is to check if p can point to q in some execution of the program. This well-studied problem plays a cruci...
Venkatesan T. Chakaravarthy
137
Voted
IPPS
2003
IEEE
15 years 6 months ago
Constrained Component Deployment in Wide-Area Networks Using AI Planning Techniques
Component-based models represent a dominant trend in the construction of wide-area network applications, making possible the integration of diverse functionality contained in modu...
Tatiana Kichkaylo, Anca-Andreea Ivan, Vijay Karamc...