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ACCV
2010
Springer
14 years 9 months ago
An Efficient RANSAC for 3D Object Recognition in Noisy and Occluded Scenes
In this paper, we present an efficient algorithm for 3D object recognition in presence of clutter and occlusions in noisy, sparse and unsegmented range data. The method uses a robu...
Chavdar Papazov, Darius Burschka
JCSS
2008
138views more  JCSS 2008»
15 years 2 months ago
Reducing mechanism design to algorithm design via machine learning
We use techniques from sample-complexity in machine learning to reduce problems of incentive-compatible mechanism design to standard algorithmic questions, for a broad class of re...
Maria-Florina Balcan, Avrim Blum, Jason D. Hartlin...
SIGIR
2009
ACM
15 years 8 months ago
SUSHI: scoring scaled samples for server selection
Modern techniques for distributed information retrieval use a set of documents sampled from each server, but these samples have been underutilised in server selection. We describe...
Paul Thomas, Milad Shokouhi
AAAI
2006
15 years 3 months ago
Sound and Efficient Inference with Probabilistic and Deterministic Dependencies
Reasoning with both probabilistic and deterministic dependencies is important for many real-world problems, and in particular for the emerging field of statistical relational lear...
Hoifung Poon, Pedro Domingos
GECCO
2006
Springer
138views Optimization» more  GECCO 2006»
15 years 6 months ago
Does overfitting affect performance in estimation of distribution algorithms
Estimation of Distribution Algorithms (EDAs) are a class of evolutionary algorithms that use machine learning techniques to solve optimization problems. Machine learning is used t...
Hao Wu, Jonathan L. Shapiro