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» Selectivity Estimation using Probabilistic Models
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UAI
2004
15 years 1 months ago
Active Model Selection
Classical learning assumes the learner is given a labeled data sample, from which it learns a model. The field of Active Learning deals with the situation where the learner begins...
Omid Madani, Daniel J. Lizotte, Russell Greiner
SRDS
2008
IEEE
15 years 6 months ago
Probabilistic Failure Detection for Efficient Distributed Storage Maintenance
Distributed storage systems often use data replication to mask failures and guarantee high data availability. Node failures can be transient or permanent. While the system must ge...
Jing Tian, Zhi Yang, Wei Chen, Ben Y. Zhao, Yafei ...
ICRA
2007
IEEE
189views Robotics» more  ICRA 2007»
15 years 6 months ago
Context Estimation and Learning Control through Latent Variable Extraction: From discrete to continuous contexts
— Recent advances in machine learning and adaptive motor control have enabled efficient techniques for online learning of stationary plant dynamics and it’s use for robust pre...
Georgios Petkos, Sethu Vijayakumar
GECCO
2008
Springer
147views Optimization» more  GECCO 2008»
15 years 29 days ago
On selecting the best individual in noisy environments
In evolutionary algorithms, the typical post-processing phase involves selection of the best-of-run individual, which becomes the final outcome of the evolutionary run. Trivial f...
Wojciech Jaskowski, Wojciech Kotlowski
FGR
2008
IEEE
117views Biometrics» more  FGR 2008»
15 years 6 months ago
Complex human motion estimation using visibility
This paper presents a novel algorithm for estimating complex human motion from 3D video. We base our algorithm on a model-based approach which uses a complete surface mesh of a 3D...
Tomoyuki Mukasa, Arata Miyamoto, Shohei Nobuhara, ...