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NIPS
1992
15 years 5 months ago
Explanation-Based Neural Network Learning for Robot Control
How can artificial neural nets generalize better from fewer examples? In order to generalize successfully, neural network learning methods typically require large training data se...
Tom M. Mitchell, Sebastian Thrun
NIPS
1998
15 years 5 months ago
Learning a Continuous Hidden Variable Model for Binary Data
A directed generative model for binary data using a small number of hidden continuous units is investigated. A clipping nonlinearity distinguishes the model from conventional prin...
Daniel D. Lee, Haim Sompolinsky
138
Voted
IEEEMM
2007
146views more  IEEEMM 2007»
15 years 4 months ago
Learning Microarray Gene Expression Data by Hybrid Discriminant Analysis
— Microarray technology offers a high throughput means to study expression networks and gene regulatory networks in cells. The intrinsic nature of high dimensionality and small s...
Yijuan Lu, Qi Tian, Maribel Sanchez, Jennifer L. N...
FC
2010
Springer
173views Cryptology» more  FC 2010»
15 years 5 months ago
A Case Study on Measuring Statistical Data in the Tor Anonymity Network
The Tor network is one of the largest deployed anonymity networks, consisting of 1500+ volunteer-run relays and probably hundreds of thousands of clients connecting every day. Its ...
Karsten Loesing, Steven J. Murdoch, Roger Dingledi...
UAI
2004
15 years 5 months ago
"Ideal Parent" Structure Learning for Continuous Variable Networks
In recent years, there is a growing interest in learning Bayesian networks with continuous variables. Learning the structure of such networks is a computationally expensive proced...
Iftach Nachman, Gal Elidan, Nir Friedman