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» On a theory of learning with similarity functions
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NPL
2000
135views more  NPL 2000»
14 years 11 months ago
Towards the Optimal Learning Rate for Backpropagation
A backpropagation learning algorithm for feedforward neural networks with an adaptive learning rate is derived. The algorithm is based upon minimising the instantaneous output erro...
Danilo P. Mandic, Jonathon A. Chambers
SIGECOM
2010
ACM
149views ECommerce» more  SIGECOM 2010»
15 years 4 months ago
A new understanding of prediction markets via no-regret learning
We explore the striking mathematical connections that exist between market scoring rules, cost function based prediction markets, and no-regret learning. We first show that any c...
Yiling Chen, Jennifer Wortman Vaughan
TREC
2003
15 years 1 months ago
Ranking Function Discovery by Genetic Programming for Robust Retrieval
Ranking functions are instrumental for the success of an information retrieval (search engine) system. However nearly all existing ranking functions are manually designed based on...
Li Wang, Weiguo Fan, Rui Yang, Wensi Xi, Ming Luo,...
MVA
2000
172views Computer Vision» more  MVA 2000»
15 years 1 months ago
Partial Face Extraction and Recognition Using Radial Basis Function Networks
work, applies a nonlinear transformation from the input space to the hidden space. The output layer Partial face images, e.g.1 eyes, nose, and ear supplies the response of the netw...
Nan He, Kiminori Sato, Yukitoshi Takahashi
ICLP
2007
Springer
15 years 6 months ago
Minimal Logic Programs
aa We consider the problem of obtaining a minimal logic program strongly equivalent (under the stable models semantics) to a given arbitrary propositional theory. We propose a meth...
Pedro Cabalar, David Pearce, Agustín Valver...