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ICML
2007
IEEE
14 years 8 months 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
14 years 8 months 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
KDD
2004
ACM
237views Data Mining» more  KDD 2004»
14 years 8 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
14 years 8 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
14 years 8 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