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» Algorithmic randomness of continuous functions
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GECCO
2010
Springer
188views Optimization» more  GECCO 2010»
15 years 1 months ago
Benchmarking real-coded genetic algorithm on noisy black-box optimization testbed
Originally, genetic algorithms were developed based on the binary representation of candidate solutions in which each conjectured solution is a fixed-length string of binary numb...
Thanh-Do Tran, Gang-Gyoo Jin
CVPR
2005
IEEE
15 years 12 months ago
Damped Newton Algorithms for Matrix Factorization with Missing Data
The problem of low-rank matrix factorization in the presence of missing data has seen significant attention in recent computer vision research. The approach that dominates the lit...
A. M. Buchanan, Andrew W. Fitzgibbon
DAGM
2008
Springer
14 years 11 months ago
MAP-Inference for Highly-Connected Graphs with DC-Programming
The design of inference algorithms for discrete-valued Markov Random Fields constitutes an ongoing research topic in computer vision. Large state-spaces, none-submodular energy-fun...
Jörg H. Kappes, Christoph Schnörr
ICIAP
2005
ACM
15 years 10 months ago
Optimal Parameter Estimation for MRF Stereo Matching
Abstract. This paper presents an optimisation technique to select automatically a set of control parameters for a Markov Random Field applied to stereo matching. The method is base...
Riccardo Gherardi, Umberto Castellani, Andrea Fusi...
CAV
2006
Springer
133views Hardware» more  CAV 2006»
15 years 1 months ago
Antichains: A New Algorithm for Checking Universality of Finite Automata
We propose and evaluate a new algorithm for checking the universality of nondeterministic finite automata. In contrast to the standard algorithm, which uses the subset construction...
Martin De Wulf, Laurent Doyen, Thomas A. Henzinger...