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IJDMB
2011
85views more  IJDMB 2011»
13 years 6 days ago
Protein interaction detection in sentences via Gaussian Processes: a preliminary evaluation
: Classification methods are vital for efficient access of knowledge hidden in biomedical publications. Support vector machines (SVMs) are modern non-parametric deterministic clas...
Tamara Polajnar, Simon Rogers, Mark Girolami
PKDD
2010
Springer
184views Data Mining» more  PKDD 2010»
13 years 3 months ago
Shift-Invariant Grouped Multi-task Learning for Gaussian Processes
Multi-task learning leverages shared information among data sets to improve the learning performance of individual tasks. The paper applies this framework for data where each task ...
Yuyang Wang, Roni Khardon, Pavlos Protopapas
ESANN
2006
13 years 6 months ago
Stochastic Processes for Canonical Correlation Analysis
We consider two stochastic process methods for performing canonical correlation analysis (CCA). The first uses a Gaussian Process formulation of regression in which we use the cur...
Colin Fyfe, Gayle Leen
JMLR
2010
118views more  JMLR 2010»
13 years 1 days ago
Dirichlet Process Mixtures of Generalized Linear Models
We propose Dirichlet Process mixtures of Generalized Linear Models (DP-GLMs), a new method of nonparametric regression that accommodates continuous and categorical inputs, models ...
Lauren Hannah, David M. Blei, Warren B. Powell
ESSMAC
2003
Springer
13 years 10 months ago
Nonlinear Predictive Control with a Gaussian Process Model
Abstract. Gaussian process models provide a probabilistic non-parametric modelling approach for black-box identification of nonlinear dynamic systems. The Gaussian processes can h...
Jus Kocijan, Roderick Murray-Smith