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ICPR
2008
IEEE
15 years 9 months ago
Semi-supervised marginal discriminant analysis based on QR decomposition
In this paper, a novel subspace learning method, semi-supervised marginal discriminant analysis (SMDA), is proposed for classification. SMDA aims at maintaining the intrinsic neig...
Rui Xiao, Pengfei Shi
GECCO
2006
Springer
159views Optimization» more  GECCO 2006»
15 years 6 months ago
Multi-step environment learning classifier systems applied to hyper-heuristics
Heuristic Algorithms (HA) are very widely used to tackle practical problems in operations research. They are simple, easy to understand and inspire confidence. Many of these HAs a...
Javier G. Marín-Blázquez, Sonia Schu...
CVPR
2006
IEEE
16 years 4 months ago
Learning Semantic Patterns with Discriminant Localized Binary Projections
In this paper, we present a novel approach to learning semantic localized patterns with binary projections in a supervised manner. The pursuit of these binary projections is refor...
Shuicheng Yan, Tianqiang Yuan, Xiaoou Tang
KDD
2009
ACM
150views Data Mining» more  KDD 2009»
16 years 3 months ago
Information theoretic regularization for semi-supervised boosting
We present novel semi-supervised boosting algorithms that incrementally build linear combinations of weak classifiers through generic functional gradient descent using both labele...
Lei Zheng, Shaojun Wang, Yan Liu, Chi-Hoon Lee
NIPS
2008
15 years 4 months ago
Privacy-preserving logistic regression
This paper addresses the important tradeoff between privacy and learnability, when designing algorithms for learning from private databases. We focus on privacy-preserving logisti...
Kamalika Chaudhuri, Claire Monteleoni