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» Learning from Highly Structured Data by Decomposition
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EUSFLAT
2003
122views Fuzzy Logic» more  EUSFLAT 2003»
14 years 11 months ago
Structure recognition on sequences with a neuro-fuzzy-system
We present a formal description of a neurofuzzy system capable of aligning two sequences recognizing their internal structure. The alignment is done on two levels: grouping of the...
Klaus Dalinghaus, Tillman Weyde
BMCBI
2006
202views more  BMCBI 2006»
14 years 10 months ago
DWARF - a data warehouse system for analyzing protein families
Background: The emerging field of integrative bioinformatics provides the tools to organize and systematically analyze vast amounts of highly diverse biological data and thus allo...
Markus Fischer, Quan K. Thai, Melanie Grieb, J&uum...
CITA
2005
IEEE
15 years 3 months ago
Cache Hierarchy Inspired Compression: a Novel Architecture for Data Streams
- We present an architecture for data streams based on structures typically found in web cache hierarchies. The main idea is to build a meta level analyser from a number of levels ...
Geoffrey Holmes, Bernhard Pfahringer, Richard Kirk...
ICDM
2006
IEEE
164views Data Mining» more  ICDM 2006»
15 years 4 months ago
Unsupervised Learning of Tree Alignment Models for Information Extraction
We propose an algorithm for extracting fields from HTML search results. The output of the algorithm is a database table– a data structure that better lends itself to high-level...
Philip Zigoris, Damian Eads, Yi Zhang
NIPS
1994
14 years 11 months ago
Factorial Learning and the EM Algorithm
Many real world learning problems are best characterized by an interaction of multiple independent causes or factors. Discovering such causal structure from the data is the focus ...
Zoubin Ghahramani