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AAAI
1994
15 years 2 months ago
Learning to Select Useful Landmarks
To navigate effectively, an autonomous agent must be able to quickly and accurately determine its current location. Given an initial estimate of its position (perhaps based on dea...
Russell Greiner, Ramana Isukapalli
CORR
2008
Springer
107views Education» more  CORR 2008»
15 years 1 months ago
A Spectral Algorithm for Learning Hidden Markov Models
Hidden Markov Models (HMMs) are one of the most fundamental and widely used statistical tools for modeling discrete time series. In general, learning HMMs from data is computation...
Daniel Hsu, Sham M. Kakade, Tong Zhang
BMCBI
2007
113views more  BMCBI 2007»
15 years 1 months ago
Learning biophysically-motivated parameters for alpha helix prediction
Background: Our goal is to develop a state-of-the-art protein secondary structure predictor, with an intuitive and biophysically-motivated energy model. We treat structure predict...
Blaise Gassend, Charles W. O'Donnell, William Thie...
TCBB
2008
120views more  TCBB 2008»
15 years 1 months ago
Learning Scoring Schemes for Sequence Alignment from Partial Examples
When aligning biological sequences, the choice of scoring scheme is critical. Even small changes in gap penalties, for example, can yield radically different alignments. A rigorous...
Eagu Kim, John D. Kececioglu
MICCAI
2010
Springer
14 years 12 months ago
Manifold Learning for Biomarker Discovery in MR Imaging
We propose a framework for the extraction of biomarkers from low-dimensional manifolds representing inter- and intra-subject brain variation in MR image data. The coordinates of ea...
Robin Wolz, Paul Aljabar, Joseph V. Hajnal, Daniel...