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» Recursive Neural Networks and Graphs: Dealing with Cycles
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ECAI
2000
Springer
13 years 8 months ago
Learning Efficiently with Neural Networks: A Theoretical Comparison between Structured and Flat Representations
Abstract. We are interested in the relationship between learning efficiency and representation in the case of supervised neural networks for pattern classification trained by conti...
Marco Gori, Paolo Frasconi, Alessandro Sperduti
NN
1997
Springer
174views Neural Networks» more  NN 1997»
13 years 9 months ago
Learning Dynamic Bayesian Networks
Bayesian networks are directed acyclic graphs that represent dependencies between variables in a probabilistic model. Many time series models, including the hidden Markov models (H...
Zoubin Ghahramani
CLUSTER
2003
IEEE
13 years 10 months ago
Compiler Optimized Remote Method Invocation
We further increase the efficiency of Java RMI programs. Where other optimizing re-implementations of RMI use pre-processors to create stubs and skeletons and to create class spe...
Ronald Veldema, Michael Philippsen
NIPS
2004
13 years 6 months ago
Large-Scale Prediction of Disulphide Bond Connectivity
The formation of disulphide bridges among cysteines is an important feature of protein structures. Here we develop new methods for the prediction of disulphide bond connectivity. ...
Pierre Baldi, Jianlin Cheng, Alessandro Vullo
INFOCOM
2010
IEEE
13 years 3 months ago
Beyond Triangle Inequality: Sifting Noisy and Outlier Distance Measurements for Localization
—Knowing accurate positions of nodes in wireless ad-hoc and sensor networks is essential for a wide range of pervasive and mobile applications. However, errors are inevitable in ...
Lirong Jian, Zheng Yang, Yunhao Liu