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TMI
2010
182views more  TMI 2010»
13 years 8 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
SBACPAD
2003
IEEE
180views Hardware» more  SBACPAD 2003»
14 years 3 months ago
New Parallel Algorithms for Frequent Itemset Mining in Very Large Databases
Frequent itemset mining is a classic problem in data mining. It is a non-supervised process which concerns in finding frequent patterns (or itemsets) hidden in large volumes of d...
Adriano Veloso, Wagner Meira Jr., Srinivasan Parth...
EPIA
2003
Springer
14 years 3 months ago
Mining Low Dimensionality Data Streams of Continuous Attributes
This paper presents an incremental and scalable learning algorithm in order to mine numeric, low dimensionality, high–cardinality, time–changing data streams. Within the Superv...
Francisco J. Ferrer-Troyano, Jesús S. Aguil...
ICPR
2010
IEEE
14 years 1 months ago
Underwater Mine Classification with Imperfect Labels
A new algorithm for performing classification with imperfectly labeled data is presented. The proposed approach is motivated by the insight that the average prediction of a group ...
David Williams
ICONIP
2008
13 years 11 months ago
A Notable Swarm Approach to Evolve Neural Network for Classification in Data Mining
This paper presents a novel and notable swarm approach to evolve an optimal set of weights and architecture of a neural network for classification in data mining. In a distributed ...
Satchidananda Dehuri, Bijan Bihari Misra, Sung-Bae...