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IBPRIA
2009
Springer
15 years 7 months ago
Inference and Learning for Active Sensing, Experimental Design and Control
In this paper we argue that maximum expected utility is a suitable framework for modeling a broad range of decision problems arising in pattern recognition and related fields. Exa...
Hendrik Kück, Matthew Hoffman, Arnaud Doucet,...
130
Voted
BMCBI
2007
197views more  BMCBI 2007»
15 years 3 months ago
Boolean networks using the chi-square test for inferring large-scale gene regulatory networks
Background: Boolean network (BN) modeling is a commonly used method for constructing gene regulatory networks from time series microarray data. However, its major drawback is that...
Haseong Kim, Jae K. Lee, Taesung Park
EMNLP
2010
15 years 28 days ago
Holistic Sentiment Analysis Across Languages: Multilingual Supervised Latent Dirichlet Allocation
In this paper, we develop multilingual supervised latent Dirichlet allocation (MLSLDA), a probabilistic generative model that allows insights gleaned from one language's data...
Jordan L. Boyd-Graber, Philip Resnik
SDM
2012
SIAM
252views Data Mining» more  SDM 2012»
13 years 5 months ago
Learning from Heterogeneous Sources via Gradient Boosting Consensus
Multiple data sources containing different types of features may be available for a given task. For instance, users’ profiles can be used to build recommendation systems. In a...
Xiaoxiao Shi, Jean-François Paiement, David...
MICCAI
2006
Springer
16 years 3 months ago
Probabilistic Brain Atlas Encoding Using Bayesian Inference
This paper addresses the problem of creating probabilistic brain atlases from manually labeled training data. We propose a general mesh-based atlas representation, and compare diff...
Koen Van Leemput