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» Learning about and through Empirical Modelling
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CP
2006
Springer
14 years 5 days ago
Performance Prediction and Automated Tuning of Randomized and Parametric Algorithms
Abstract. Machine learning can be utilized to build models that predict the runtime of search algorithms for hard combinatorial problems. Such empirical hardness models have previo...
Frank Hutter, Youssef Hamadi, Holger H. Hoos, Kevi...
CVPR
2010
IEEE
14 years 4 months ago
Learning Mid-Level Features For Recognition
Many successful models for scene or object recognition transform low-level descriptors (such as Gabor filter responses, or SIFT descriptors) into richer representations of interme...
Y-Lan Boureau, Francis Bach, Yann LeCun, Jean Ponc...
DICTA
2003
13 years 9 months ago
Learning Semantic Concepts from Visual Data Using Neural Networks
For content-based image retrieval techniques, query image is used to pick up and rank some relevant images from a database using some certain similarity metric. If semantic feature...
Xiaohang Ma, Dianhui Wang
ICDM
2008
IEEE
113views Data Mining» more  ICDM 2008»
14 years 2 months ago
Online Reliability Estimates for Individual Predictions in Data Streams
Several predictive systems are nowadays vital for operations and decision support. The quality of these systems is most of the time defined by their average accuracy which has lo...
Pedro Pereira Rodrigues, João Gama, Zoran B...
LION
2007
Springer
192views Optimization» more  LION 2007»
14 years 2 months ago
Learning While Optimizing an Unknown Fitness Surface
This paper is about Reinforcement Learning (RL) applied to online parameter tuning in Stochastic Local Search (SLS) methods. In particular a novel application of RL is considered i...
Roberto Battiti, Mauro Brunato, Paolo Campigotto