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» Learning Functions from Imperfect Positive Data
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NIPS
2003
15 years 4 months ago
Semi-Supervised Learning with Trees
We describe a nonparametric Bayesian approach to generalizing from few labeled examples, guided by a larger set of unlabeled objects and the assumption of a latent tree-structure ...
Charles Kemp, Thomas L. Griffiths, Sean Stromsten,...
153
Voted
CVPR
2009
IEEE
16 years 10 months ago
Learning Invariant Features Through Topographic Filter Maps
Several recently-proposed architectures for highperformance object recognition are composed of two main stages: a feature extraction stage that extracts locallyinvariant feature...
Koray Kavukcuoglu, Marc'Aurelio Ranzato, Rob Fergu...
139
Voted
CEC
2010
IEEE
15 years 4 months ago
Adaptive learning particle swarm optimizer-II for global optimization
This paper presents an updated version of the adaptive learning particle swarm optimizer (ALPSO) [6], we call it ALPSO-II. In order to improve the performance of ALPSO on multi-mod...
Changhe Li, Shengxiang Yang
160
Voted
ICML
1999
IEEE
16 years 4 months ago
Least-Squares Temporal Difference Learning
Excerpted from: Boyan, Justin. Learning Evaluation Functions for Global Optimization. Ph.D. thesis, Carnegie Mellon University, August 1998. (Available as Technical Report CMU-CS-...
Justin A. Boyan
ICDAR
2009
IEEE
15 years 10 months ago
Statistical Modeling and Learning for Recognition-Based Handwritten Numeral String Segmentation
This paper proposes a recognition based approach to handwritten numeral string segmentation. We consider two classes: numeral strings segmented correctly or not. The feature vecto...
Yanjie Wang, Xiabi Liu, Yunde Jia