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» Variations on U-Shaped Learning
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WSC
1998
13 years 9 months ago
Integrating Neural Networks with Special Purpose Simulation
Traditional methods of dealing with variability in simulation input data are mainly stochastic. This is most often the best method to use if the factors affecting the variation or...
Dany Hajjar, Simaan M. AbouRizk, Kevin Mather
NIPS
1993
13 years 9 months ago
Analyzing Cross-Connected Networks
The non-linear complexities of neural networks make network solutions difficult to understand. Sanger's contribution analysis is here extended to the analysis of networks aut...
Thomas R. Shultz, Jeffrey L. Elman
ANLP
1992
86views more  ANLP 1992»
13 years 9 months ago
A Simple Rule-Based Part of Speech Tagger
Automatic part of speech tagging is an area of natural language processing where statistical techniques have been more successful than rule-based methods. In this paper, we presen...
Eric Brill
ECCV
2010
Springer
13 years 9 months ago
Robust and Fast Collaborative Tracking with Two Stage Sparse Optimization
Abstract. The sparse representation has been widely used in many areas and utilized for visual tracking. Tracking with sparse representation is formulated as searching for samples ...
Baiyang Liu, Lin Yang, Junzhou Huang, Peter Meer, ...
DAGM
2010
Springer
13 years 8 months ago
Complex Motion Models for Simple Optical Flow Estimation
The selection of an optical flow method is mostly a choice from among accuracy, efficiency and ease of implementation. While variational approaches tend to be more accurate than lo...
Claudia Nieuwenhuis, Daniel Kondermann, Christoph ...