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ECCV
2010
Springer
15 years 3 months ago
MIForests: Multiple-Instance Learning with Randomized Trees
Abstract. Multiple-instance learning (MIL) allows for training classifiers from ambiguously labeled data. In computer vision, this learning paradigm has been recently used in many ...
Christian Leistner, Amir Saffari, Horst Bischof
PPSN
2004
Springer
15 years 8 months ago
Optimization via Parameter Mapping with Genetic Programming
Abstract. This paper describes a new approach for parameter optimization that uses a novel representation for the parameters to be optimized. By using genetic programming, the new ...
João Carlos Figueira Pujol, Riccardo Poli
GECCO
2000
Springer
121views Optimization» more  GECCO 2000»
15 years 6 months ago
Informed operators: Speeding up genetic-algorithm-based design optimization using reduced models
In this paper we describe a method for improving genetic-algorithm-based optimization using informed genetic operators. The idea is to make the genetic operators such as mutation ...
Khaled Rasheed, Haym Hirsh
CISS
2007
IEEE
15 years 9 months ago
Towards Optimal Design of Data Hiding Algorithms Against Nonparametric Adversary Models
Abstract—This paper presents a novel zero-sum watermarking game between a detection algorithm and a data hiding adversary. Contrary to previous research, the detection algorithm ...
Alvaro A. Cárdenas, George V. Moustakides, ...
PPSN
2000
Springer
15 years 6 months ago
Practical Implications of New Results in Conservation of Optimizer Performance
Abstract. Three theoretical perspectives upon conservation of performance in function optimization are outlined. In terms of statistical information, performance is conserved when ...
Thomas M. English