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JMLR
2008
159views more  JMLR 2008»
15 years 1 months ago
Near-Optimal Sensor Placements in Gaussian Processes: Theory, Efficient Algorithms and Empirical Studies
When monitoring spatial phenomena, which can often be modeled as Gaussian processes (GPs), choosing sensor locations is a fundamental task. There are several common strategies to ...
Andreas Krause, Ajit Paul Singh, Carlos Guestrin
SDM
2004
SIAM
211views Data Mining» more  SDM 2004»
15 years 2 months ago
Using Support Vector Machines for Classifying Large Sets of Multi-Represented Objects
Databases are a key technology for molecular biology which is a very data intensive discipline. Since molecular biological databases are rather heterogeneous, unification and data...
Hans-Peter Kriegel, Peer Kröger, Alexey Pryak...
BMCBI
2006
150views more  BMCBI 2006»
15 years 1 months ago
Predicting protein subcellular locations using hierarchical ensemble of Bayesian classifiers based on Markov chains
Background: The subcellular location of a protein is closely related to its function. It would be worthwhile to develop a method to predict the subcellular location for a given pr...
Alla Bulashevska, Roland Eils
ICIAR
2009
Springer
15 years 8 months ago
Interactive Image Segmentation Based on Hierarchical Graph-Cut Optimization with Generic Shape Prior
Abstract. A new algorithm for interactive image segmentation is proposed. Besides the traditional appearance and gradient information, a new Generic Shape Prior (GSP) knowledge whi...
Chen Liu, Fengxia Li, Yan Zhang, Haiyang Gu
NIPS
2007
15 years 2 months ago
Hierarchical Penalization
Hierarchical penalization is a generic framework for incorporating prior information in the fitting of statistical models, when the explicative variables are organized in a hiera...
Marie Szafranski, Yves Grandvalet, Pierre Morizet-...