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» Measuring the Complexity of Classification Problems
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NIPS
1994
13 years 9 months ago
Efficient Methods for Dealing with Missing Data in Supervised Learning
We present efficient algorithms for dealing with the problem of missing inputs (incomplete feature vectors) during training and recall. Our approach is based on the approximation ...
Volker Tresp, Ralph Neuneier, Subutai Ahmad
COMPUTING
2006
119views more  COMPUTING 2006»
13 years 8 months ago
Sparse Grids, Adaptivity, and Symmetry
Sparse grid methods represent a powerful and efficient technique for the representation and approximation of functions and particularly the solutions of partial differential equat...
Harry Yserentant
TNN
2008
143views more  TNN 2008»
13 years 8 months ago
Blur Identification by Multilayer Neural Network Based on Multivalued Neurons
A multilayer neural network based on multivalued neurons (MLMVN) is a neural network with a traditional feedforward architecture. At the same time, this network has a number of spe...
Igor N. Aizenberg, Dmitriy Paliy, Jacek M. Zurada,...
ACL
2010
13 years 3 months ago
Adapting Self-Training for Semantic Role Labeling
Supervised semantic role labeling (SRL) systems trained on hand-crafted annotated corpora have recently achieved state-of-the-art performance. However, creating such corpora is te...
Rasoul Samad Zadeh Kaljahi
SIAMJO
2010
136views more  SIAMJO 2010»
13 years 2 months ago
A New Exchange Method for Convex Semi-Infinite Programming
In this paper we propose a new exchange method for solving convex semi-infinite programming (CSIP) problems. We introduce a new dropping-rule in the proposed exchange algorithm, wh...
Liping Zhang, Soon-Yi Wu, Marco A. López