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ICML
2008
IEEE
16 years 7 months ago
Sequence kernels for predicting protein essentiality
The problem of identifying the minimal gene set required to sustain life is of crucial importance in understanding cellular mechanisms and designing therapeutic drugs. This work d...
Cyril Allauzen, Mehryar Mohri, Ameet Talwalkar
ICML
2008
IEEE
16 years 7 months ago
Active kernel learning
Identifying the appropriate kernel function/matrix for a given dataset is essential to all kernel-based learning techniques. A variety of kernel learning algorithms have been prop...
Steven C. H. Hoi, Rong Jin
ICML
2006
IEEE
16 years 7 months ago
A graphical model for predicting protein molecular function
We present a simple statistical model of molecular function evolution to predict protein function. The model description encodes general knowledge of how molecular function evolve...
Barbara E. Engelhardt, Michael I. Jordan, Steven E...
ICML
2006
IEEE
16 years 7 months ago
Kernel Predictive Linear Gaussian models for nonlinear stochastic dynamical systems
The recent Predictive Linear Gaussian model (or PLG) improves upon traditional linear dynamical system models by using a predictive representation of state, which makes consistent...
David Wingate, Satinder P. Singh
ICML
2005
IEEE
16 years 7 months ago
Optimal assignment kernels for attributed molecular graphs
We propose a new kernel function for attributed molecular graphs, which is based on the idea of computing an optimal assignment from the atoms of one molecule to those of another ...
Andreas Zell, Florian Sieker, Holger Fröhlich...