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» A Minimax Method for Learning Functional Networks
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NPL
2006
172views more  NPL 2006»
13 years 7 months ago
Adapting RBF Neural Networks to Multi-Instance Learning
In multi-instance learning, the training examples are bags composed of instances without labels, and the task is to predict the labels of unseen bags through analyzing the training...
Min-Ling Zhang, Zhi-Hua Zhou
ICML
2006
IEEE
14 years 8 months ago
Cost-sensitive learning with conditional Markov networks
There has been a recent, growing interest in classification and link prediction in structured domains. Methods such as conditional random fields and relational Markov networks sup...
Prithviraj Sen, Lise Getoor
IJON
2007
184views more  IJON 2007»
13 years 7 months ago
Convex incremental extreme learning machine
Unlike the conventional neural network theories and implementations, Huang et al. [Universal approximation using incremental constructive feedforward networks with random hidden n...
Guang-Bin Huang, Lei Chen
SBRN
2008
IEEE
14 years 1 months ago
Imitation Learning of an Intelligent Navigation System for Mobile Robots Using Reservoir Computing
The design of an autonomous navigation system for mobile robots can be a tough task. Noisy sensors, unstructured environments and unpredictability are among the problems which mus...
Eric A. Antonelo, Benjamin Schrauwen, Dirk Strooba...
ICC
2007
IEEE
120views Communications» more  ICC 2007»
14 years 1 months ago
Dynamic Network Selection using Kernels
—We present a new algorithm for vertical handover and dynamic network selection, based on a combination of multiattribute utility theory, kernel learning and stochastic gradient ...
Eric van den Berg, Praveen Gopalakrishnan, Byungsu...