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» Learning with Annotation Noise
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113
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ESANN
2003
15 years 5 months ago
Robust Topology Representing Networks
Martinetz and Schulten proposed the use of a Competitive Hebbian Learning (CHL) rule to build Topology Representing Networks. From a set of units and a data distribution, a link i...
Michaël Aupetit
108
Voted
GECCO
2004
Springer
127views Optimization» more  GECCO 2004»
15 years 9 months ago
Improved Niching and Encoding Strategies for Clustering Noisy Data Sets
Clustering is crucial to many applications in pattern recognition, data mining, and machine learning. Evolutionary techniques have been used with success in clustering, but most su...
Olfa Nasraoui, Elizabeth Leon
PAKDD
2000
ACM
100views Data Mining» more  PAKDD 2000»
15 years 7 months ago
Discovery of Relevant Weights by Minimizing Cross-Validation Error
In order to discover relevant weights of neural networks, this paper proposes a novel method to learn a distinct squared penalty factor for each weight as a minimization problem ov...
Kazumi Saito, Ryohei Nakano
PR
2006
99views more  PR 2006»
15 years 3 months ago
Multisets mixture learning-based ellipse detection
We develop an ellipse detection algorithm based on the multisets mixture learning (MML) that differs from the conventional Hough transform perspective. The algorithm developed has...
Zhiyong Liu, Hong Qiao, Lei Xu
RFIDSEC
2010
15 years 1 months ago
Tree-Based RFID Authentication Protocols Are Definitively Not Privacy-Friendly
Authentication for low-cost Radio-Frequency IDentification (RFID) is a booming research topic. The challenge is to develop secure protocols using lightweight cryptography, yet ensu...
Gildas Avoine, Benjamin Martin 0002, Tania Martin