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ICANN
2009
Springer
15 years 2 months ago
An EM Based Training Algorithm for Recurrent Neural Networks
Recurrent neural networks serve as black-box models for nonlinear dynamical systems identification and time series prediction. Training of recurrent networks typically minimizes t...
Jan Unkelbach, Yi Sun, Jürgen Schmidhuber
TSE
2002
96views more  TSE 2002»
14 years 9 months ago
Better Reliability Assessment and Prediction through Data Clustering
This paper presents a new approach to software reliability modeling by grouping data into clusters of homogeneous failure intensities. This series of data clusters associated with...
Jeff Tian
99
Voted
TITB
2010
123views Education» more  TITB 2010»
14 years 4 months ago
The pseudotemporal bootstrap for predicting glaucoma from cross-sectional visual field data
Progressive loss of the field of vision is characteristic of a number of eye diseases such as glaucoma, a leading cause of irreversible blindness in the world. Recently, there has ...
Allan Tucker, David Garway-Heath
IEEEPACT
2008
IEEE
15 years 3 months ago
Characterizing and modeling the behavior of context switch misses
One of the essential features in modern computer systems is context switching, which allows multiple threads of execution to time-share a limited number of processors. While very ...
Fang Liu, Fei Guo, Yan Solihin, Seongbeom Kim, Abd...
93
Voted
ASC
2000
14 years 10 months ago
Extended Neural Model Predictive Control of Non-Linear Systems
A neural model-based predictive control scheme is proposed for dealing with steady-state offsets found in standard MPC schemes. This structure is based on a constrained local inst...
P. Gil, J. Henriques, A. Dourado, H. Duarte-Ramos