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» Statistical Methods for Construction of Neural Networks
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NIPS
1998
13 years 10 months ago
Controlling the Complexity of HMM Systems by Regularization
This paper introduces a method for regularization of HMM systems that avoids parameter overfitting caused by insufficient training data. Regularization is done by augmenting the E...
Christoph Neukirchen, Gerhard Rigoll
SP
2008
IEEE
159views Security Privacy» more  SP 2008»
13 years 8 months ago
Inferring neuronal network connectivity from spike data: A temporal data mining approach
Abstract. Understanding the functioning of a neural system in terms of its underlying circuitry is an important problem in neuroscience. Recent developments in electrophysiology an...
Debprakash Patnaik, P. S. Sastry, K. P. Unnikrishn...
INFOCOM
2003
IEEE
14 years 1 months ago
Pseudo Likelihood Estimation in Network Tomography
Abstract— Network monitoring and diagnosis are key to improving network performance. The difficulties of performance monitoring lie in today’s fast growing Internet, accompani...
Gang Liang, Bin Yu
WINE
2005
Springer
268views Economy» more  WINE 2005»
14 years 2 months ago
Mining Stock Market Tendency Using GA-Based Support Vector Machines
In this study, a hybrid intelligent data mining methodology, genetic algorithm based support vector machine (GASVM) model, is proposed to explore stock market tendency. In this hyb...
Lean Yu, Shouyang Wang, Kin Keung Lai
ICPR
2010
IEEE
13 years 7 months ago
Data-Driven Lung Nodule Models for Robust Nodule Detection in Chest CT
The quality of the lung nodule models determines the success of lung nodule detection. This paper describes aspects of our data-driven approach for modeling lung nodules using the...
Amal Farag, James Graham, Aly A. Farag