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ICML
1994
IEEE
15 years 7 months ago
Hierarchical Self-Organization in Genetic programming
This paper presents an approach to automatic discovery of functions in Genetic Programming. The approach is based on discovery of useful building blocks by analyzing the evolution...
Justinian P. Rosca, Dana H. Ballard
NIPS
2003
15 years 5 months ago
Gaussian Process Latent Variable Models for Visualisation of High Dimensional Data
In this paper we introduce a new underlying probabilistic model for principal component analysis (PCA). Our formulation interprets PCA as a particular Gaussian process prior on a ...
Neil D. Lawrence
CRYPTO
2010
Springer
188views Cryptology» more  CRYPTO 2010»
15 years 4 months ago
Efficient Indifferentiable Hashing into Ordinary Elliptic Curves
Abstract. We provide the first construction of a hash function into ordinary elliptic curves that is indifferentiable from a random oracle, based on Icart's deterministic enco...
Eric Brier, Jean-Sébastien Coron, Thomas Ic...
IJON
2002
123views more  IJON 2002»
15 years 3 months ago
N-bit parity neural networks: new solutions based on linear programming
In this paper, the N-bit parity problem is solved with a neural network that allows direct connections between the input layer and the output layer. The activation function used i...
Derong Liu, Myron E. Hohil, Stanley H. Smith
ICONIP
2009
15 years 1 months ago
Learning Gaussian Process Models from Uncertain Data
It is generally assumed in the traditional formulation of supervised learning that only the outputs data are uncertain. However, this assumption might be too strong for some learni...
Patrick Dallaire, Camille Besse, Brahim Chaib-draa