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74
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ICML
2007
IEEE
16 years 7 days ago
Linear and nonlinear generative probabilistic class models for shape contours
We introduce a robust probabilistic approach to modeling shape contours based on a lowdimensional, nonlinear latent variable model. In contrast to existing techniques that use obj...
Graham McNeill, Sethu Vijayakumar
ICML
2005
IEEE
16 years 7 days ago
A smoothed boosting algorithm using probabilistic output codes
AdaBoost.OC has shown to be an effective method in boosting "weak" binary classifiers for multi-class learning. It employs the Error Correcting Output Code (ECOC) method...
Rong Jin, Jian Zhang
94
Voted
KDD
2004
ACM
237views Data Mining» more  KDD 2004»
15 years 12 months ago
Bayesian Model-Averaging in Unsupervised Learning From Microarray Data
Unsupervised identification of patterns in microarray data has been a productive approach to uncovering relationships between genes and the biological process in which they are in...
Mario Medvedovic, Junhai Guo
RECOMB
2008
Springer
15 years 11 months ago
High-Resolution Modeling of Cellular Signaling Networks
A central challenge in systems biology is the reconstruction of biological networks from high-throughput data sets. A particularly difficult case of this is the inference of dynami...
Michael Baym, Chris Bakal, Norbert Perrimon, Bonni...
RECOMB
2003
Springer
15 years 11 months ago
On de novo interpretation of tandem mass spectra for peptide identification
The correct interpretation of tandem mass spectra is a difficult problem, even when it is limited to scoring peptides against a database. De novo sequencing is considerably harder...
Vineet Bafna, Nathan Edwards