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» Learning programs from noisy data
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RECOMB
2000
Springer
15 years 6 months ago
Using Bayesian networks to analyze expression data
DNA hybridization arrays simultaneously measure the expression level for thousands of genes. These measurements provide a "snapshot" of transcription levels within the c...
Nir Friedman, Michal Linial, Iftach Nachman, Dana ...
NPL
2006
85views more  NPL 2006»
15 years 2 months ago
A Neural Model for Context-dependent Sequence Learning
A novel neural network model is described that implements context-dependent learning of complex sequences. The model utilises leaky integrate-and-fire neurons to extract timing inf...
Luc Berthouze, Adriaan G. Tijsseling
153
Voted
CVPR
2012
IEEE
13 years 4 months ago
Image denoising: Can plain neural networks compete with BM3D?
Image denoising can be described as the problem of mapping from a noisy image to a noise-free image. The best currently available denoising methods approximate this mapping with c...
Harold Christopher Burger, Christian J. Schuler, S...
180
Voted
MLG
2007
Springer
15 years 8 months ago
Abductive Stochastic Logic Programs for Metabolic Network Inhibition Learning
Abstract. We revisit an application developed originally using Inductive Logic Programming (ILP) by replacing the underlying Logic Program (LP) description with Stochastic Logic Pr...
Jianzhong Chen, Stephen Muggleton, Jose Santos
IJCAI
2007
15 years 3 months ago
A Fully Connectionist Model Generator for Covered First-Order Logic Programs
We present a fully connectionist system for the learning of first-order logic programs and the generation of corresponding models: Given a program and a set of training examples,...
Sebastian Bader, Pascal Hitzler, Steffen Höll...