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TMM
2002
104views more  TMM 2002»
15 years 6 months ago
Spatial contextual classification and prediction models for mining geospatial data
Modeling spatial context (e.g., autocorrelation) is a key challenge in classification problems that arise in geospatial domains. Markov random fields (MRF) is a popular model for i...
Shashi Shekhar, Paul R. Schrater, Ranga Raju Vatsa...
PKDD
2010
Springer
313views Data Mining» more  PKDD 2010»
15 years 5 months ago
Topic Modeling for Personalized Recommendation of Volatile Items
One of the major strengths of probabilistic topic modeling is the ability to reveal hidden relations via the analysis of co-occurrence patterns on dyadic observations, such as docu...
Maks Ovsjanikov, Ye Chen
TMI
2010
182views more  TMI 2010»
15 years 5 months ago
A Bayesian Mixture Approach to Modeling Spatial Activation Patterns in Multisite fMRI Data
Abstract—We propose a probabilistic model for analyzing spatial activation patterns in multiple functional magnetic resonance imaging (fMRI) activation images such as repeated ob...
Seyoung Kim, Padhraic Smyth, Hal S. Stern
INTERSPEECH
2010
15 years 1 months ago
Dynamic model selection for spectral voice conversion
Statistical methods for voice conversion are usually based on a single model selected in order to represent a tradeoff between goodness of fit and complexity. In this paper we ass...
Pierre Lanchantin, Xavier Rodet
ICASSP
2011
IEEE
14 years 10 months ago
Evaluating music sequence models through missing data
Building models of the structure in musical signals raises the question of how to evaluate and compare different modeling approaches. One possibility is to use the model to impute...
Thierry Bertin-Mahieux, Graham Grindlay, Ron J. We...