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» Data Mining via Support Vector Machines
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CGA
1999
15 years 3 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»
16 years 4 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
15 years 5 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»
15 years 4 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
15 years 5 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...