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PAMI
2006
206views more  PAMI 2006»
15 years 6 months ago
MILES: Multiple-Instance Learning via Embedded Instance Selection
Multiple-instance problems arise from the situations where training class labels are attached to sets of samples (named bags), instead of individual samples within each bag (called...
Yixin Chen, Jinbo Bi, James Ze Wang
ML
2000
ACM
244views Machine Learning» more  ML 2000»
15 years 6 months ago
Learnable Evolution Model: Evolutionary Processes Guided by Machine Learning
A new class of evolutionary computation processes is presented, called Learnable Evolution Model or LEM. In contrast to Darwinian-type evolution that relies on mutation, recombinat...
Ryszard S. Michalski
ML
2007
ACM
144views Machine Learning» more  ML 2007»
15 years 6 months ago
Invariant kernel functions for pattern analysis and machine learning
In many learning problems prior knowledge about pattern variations can be formalized and beneficially incorporated into the analysis system. The corresponding notion of invarianc...
Bernard Haasdonk, Hans Burkhardt
SAB
2010
Springer
226views Optimization» more  SAB 2010»
15 years 5 months ago
Distributed Online Learning of Central Pattern Generators in Modular Robots
Abstract. In this paper we study distributed online learning of locomotion gaits for modular robots. The learning is based on a stochastic approximation method, SPSA, which optimiz...
David Johan Christensen, Alexander Spröwitz, ...
CVPR
2009
IEEE
17 years 20 days ago
Learning Mixed Templates for Object Recognition
This article proposes a method for learning object templates composed of local sketches and local textures, and investigates the relative importance of the sketches and textures ...
Haifeng Gong, Song Chun Zhu, Ying Nian Wu, Zhangzh...