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COLING
1992
15 years 5 months ago
Syntactic Ambiguity Resolution Using A Discrimination and Robustness Oriented Adaptive Learning Algorithm
In this paper, a discrimination and robusmess oriented adaptive learning procedure is proposed to deal with the task of syntactic ambiguity resolution. Owing to the problem of ins...
Tung-Hui Chiang, Yi-Chung Lin, Keh-Yih Su
JMLR
2002
106views more  JMLR 2002»
15 years 4 months ago
Some Greedy Learning Algorithms for Sparse Regression and Classification with Mercer Kernels
We present some greedy learning algorithms for building sparse nonlinear regression and classification models from observational data using Mercer kernels. Our objective is to dev...
Prasanth B. Nair, Arindam Choudhury 0002, Andy J. ...
CVPR
2012
IEEE
13 years 6 months ago
Learning to segment dense cell nuclei with shape prior
We study the problem of segmenting multiple cell nuclei from GFP or Hoechst stained microscope images with a shape prior. This problem is encountered ubiquitously in cell biology ...
Xinghua Lou, Ullrich Köthe, Jochen Wittbrodt,...
NN
2006
Springer
15 years 4 months ago
Machine learning in soil classification
In a number of engineering problems, e.g. in geotechnics, petroleum engineering, etc. intervals of measured series data (signals) are to be attributed a class maintaining the cons...
Biswanath Bhattacharya, Dimitri P. Solomatine
SIGKDD
2000
112views more  SIGKDD 2000»
15 years 4 months ago
Artificial Neural Networks - A Science in Trouble
This article points out some very serious misconceptions about the brain in connectionism and artificial neural networks. Some of the connectionist ideas have been shown to have l...
Asim Roy