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» Data Mining via Support Vector Machines
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CGA
1999
14 years 9 months ago
Visualizing Large Telecommunication Data Sets
displays to abstract network data and let users interactwithit.Wehaveimplementedafull-scaleSwift3D prototype, which generated the examples we present here. Swift-3D We developed Sw...
Eleftherios Koutsofios, Stephen C. North, Daniel A...
SIGMOD
2004
ACM
162views Database» more  SIGMOD 2004»
15 years 10 months ago
Graph Indexing: A Frequent Structure-based Approach
Graph has become increasingly important in modelling complicated structures and schemaless data such as proteins, chemical compounds, and XML documents. Given a graph query, it is...
Xifeng Yan, Philip S. Yu, Jiawei Han
NIPS
2000
14 years 11 months ago
A New Approximate Maximal Margin Classification Algorithm
A new incremental learning algorithm is described which approximates the maximal margin hyperplane w.r.t. norm p 2 for a set of linearly separable data. Our algorithm, called alm...
Claudio Gentile
BMCBI
2007
154views more  BMCBI 2007»
14 years 10 months ago
Classification of heterogeneous microarray data by maximum entropy kernel
Background: There is a large amount of microarray data accumulating in public databases, providing various data waiting to be analyzed jointly. Powerful kernel-based methods are c...
Wataru Fujibuchi, Tsuyoshi Kato
AIME
2009
Springer
14 years 11 months ago
Learning Approach to Analyze Tumour Heterogeneity in DCE-MRI Data During Anti-cancer Treatment
Abstract. The paper proposes a learning approach to support medical researchers in the context of in-vivo cancer imaging, and specifically in the analysis of Dynamic Contrast-Enhan...
Alessandro Daducci, Umberto Castellani, Marco Cris...