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COLT
2005
Springer
14 years 1 months ago
Towards a Theoretical Foundation for Laplacian-Based Manifold Methods
In recent years manifold methods have attracted a considerable amount of attention in machine learning. However most algorithms in that class may be termed ā€œmanifold-motivatedā€...
Mikhail Belkin, Partha Niyogi
DEXA
2009
Springer
175views Database» more  DEXA 2009»
14 years 2 months ago
RoK: Roll-Up with the K-Means Clustering Method for Recommending OLAP Queries
Dimension hierarchies represent a substantial part of the data warehouse model. Indeed they allow decision makers to examine data at diļ¬€erent levels of detail with On-Line Analyt...
Fadila Bentayeb, Cécile Favre
EUROGP
2010
Springer
166views Optimization» more  EUROGP 2010»
14 years 19 days ago
Learning a Lot from Only a Little: Genetic Programming for Panel Segmentation on Sparse Sensory Evaluation Data
We describe a data mining framework that derives panelist information from sparse ļ¬‚avour survey data. One component of the framework executes genetic programming ensemble based s...
Katya Vladislavleva, Kalyan Veeramachaneni, Una-Ma...
SEMWEB
2010
Springer
13 years 5 months ago
Supporting Natural Language Processing with Background Knowledge: Coreference Resolution Case
Systems based on statistical and machine learning methods have been shown to be extremely effective and scalable for the analysis of large amount of textual data. However, in the r...
Volha Bryl, Claudio Giuliano, Luciano Serafini, Ka...
NC
2007
129views Neural Networks» more  NC 2007»
13 years 7 months ago
Sorting of neural spikes: When wavelet based methods outperform principal component analysis
Sorting of the extracellularly recorded spikes is a basic prerequisite for analysis of the cooperative neural behavior and neural code. Fundamentally the sorting performance is deļ...
Alexey N. Pavlov, Valeri A. Makarov, Ioulia Makaro...