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» Generalization Error Bounds Using Unlabeled Data
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ML
2006
ACM
110views Machine Learning» more  ML 2006»
14 years 9 months ago
Classification-based objective functions
Backpropagation, similar to most learning algorithms that can form complex decision surfaces, is prone to overfitting. This work presents classification-based objective functions, ...
Michael Rimer, Tony Martinez
DEXA
2003
Springer
149views Database» more  DEXA 2003»
15 years 3 months ago
Capturing Uncertainty in Spatial Queries over Imprecise Data
Emerging applications using miniature electronic devices (e.g., tracking mobile objects using sensors) generate very large amounts of highly dynamic data that poses very high overh...
Xingbo Yu, Sharad Mehrotra
VLDB
1998
ACM
111views Database» more  VLDB 1998»
15 years 2 months ago
Filtering with Approximate Predicates
Approximate predicates can be used to reduce the number of comparisons made by expensive, complex predicates. For example, to check if a point is within a region (expensive predic...
Narayanan Shivakumar, Hector Garcia-Molina, Chandr...
STORAGESS
2006
ACM
15 years 3 months ago
Using free web storage for data backup
Backing up important data is crucial. A variety of causes can lead to data loss, such as disk failures, administration errors, virus infiltration, theft, and physical damage to e...
Avishay Traeger, Nikolai Joukov, Josef Sipek, Erez...
IJCNN
2006
IEEE
15 years 3 months ago
Particle Swarm Optimization of Fuzzy ARTMAP Parameters
— In this paper a Particle Swarm Optimization (PSO)-based training strategy is introduced for fuzzy ARTMAP that minimizes generalization error while optimizing parameter values. ...
Eric Granger, Philippe Henniges, Luiz S. Oliveira,...