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BIBM
2008
IEEE
172views Bioinformatics» more  BIBM 2008»
15 years 11 months ago
Boosting Methods for Protein Fold Recognition: An Empirical Comparison
Protein fold recognition is the prediction of protein’s tertiary structure (Fold) given the protein’s sequence without relying on sequence similarity. Using machine learning t...
Yazhene Krishnaraj, Chandan K. Reddy
ACL
2012
13 years 7 months ago
Prediction of Learning Curves in Machine Translation
Parallel data in the domain of interest is the key resource when training a statistical machine translation (SMT) system for a specific purpose. Since ad-hoc manual translation c...
Prasanth Kolachina, Nicola Cancedda, Marc Dymetman...
147
Voted
PROCEDIA
2010
138views more  PROCEDIA 2010»
14 years 11 months ago
Using the reconfigurable massively parallel architecture COPACOBANA 5000 for applications in bioinformatics
Currently several computational problems require high processing power to handle huge amounts of data, although underlying core algorithms appear to be rather simple. Especially i...
Lars Wienbrandt, Stefan Baumgart, Jost Bissel, Car...
146
Voted
JMLR
2012
13 years 7 months ago
Bayesian Comparison of Machine Learning Algorithms on Single and Multiple Datasets
We propose a new method for comparing learning algorithms on multiple tasks which is based on a novel non-parametric test that we call the Poisson binomial test. The key aspect of...
Alexandre Lacoste, François Laviolette, Mar...
IISWC
2006
IEEE
15 years 10 months ago
An Architectural Characterization Study of Data Mining and Bioinformatics Workloads
— Data mining is the process of automatically finding implicit, previously unknown, and potentially useful information from large volumes of data. Recent advances in data extrac...
Berkin Özisikyilmaz, Ramanathan Narayanan, Jo...