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» Scalable, updatable predictive models for sequence data
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ICMCS
2005
IEEE
109views Multimedia» more  ICMCS 2005»
14 years 2 months ago
An Efficient Architecture for Lifting-Based Forward and Inverse Discrete Wavelet Transform
In this research, an architecture that performs both forward and inverse lifting-based discrete wavelet transform is proposed. The proposed architecture reduces the hardware requi...
S. Mayilavelane Aroutchelvame, Kaamran Raahemifar
ISMB
2000
13 years 10 months ago
A Probabilistic Learning Approach to Whole-Genome Operon Prediction
We present a computational approach to predicting operons in the genomes of prokaryotic organisms. Our approach uses machine learning methods to induce predictive models for this ...
Mark Craven, David Page, Jude W. Shavlik, Joseph B...
COORDINATION
2007
Springer
14 years 3 months ago
Reactors: A Data-Oriented Synchronous/Asynchronous Programming Model for Distributed Applications
Our aim is to define the kernel of a simple and uniform programming model—the reactor model—suitable for building and evolving internet-scale programs. A reactor consists of t...
John Field, Maria-Cristina V. Marinescu, Christian...
CEC
2005
IEEE
14 years 2 months ago
Evolving hidden Markov models for protein secondary structure prediction
New results are presented for the prediction of secondary structure information for protein sequences using Hidden Markov Models (HMMs) evolved using a Genetic Algorithm (GA). We a...
Kyoung-Jae Won, Thomas Hamelryck, Adam Prügel...
SGAI
2007
Springer
14 years 3 months ago
Learning Sets of Sub-Models for Spatio-Temporal Prediction
In this paper we describe a novel technique which implements a spatiotemporal model as a set of sub-models based on first order logic. These sub-models model different, typicall...
Andrew Bennett, Derek R. Magee