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106
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TACAS
2007
Springer
74views Algorithms» more  TACAS 2007»
15 years 8 months ago
Shape Analysis by Graph Decomposition
Abstract. Programs commonly maintain multiple linked data structures. Correlations between multiple data structures may often be nonexistent or irrelevant to verifying that the pro...
Roman Manevich, Josh Berdine, Byron Cook, G. Ramal...
113
Voted
WG
2007
Springer
15 years 8 months ago
On Finding Graph Clusterings with Maximum Modularity
Modularity is a recently introduced quality measure for graph clusterings. It has immediately received considerable attention in several disciplines, and in particular in the compl...
Ulrik Brandes, Daniel Delling, Marco Gaertler, Rob...
SDM
2008
SIAM
120views Data Mining» more  SDM 2008»
15 years 4 months ago
Spatial Scan Statistics for Graph Clustering
In this paper, we present a measure associated with detection and inference of statistically anomalous clusters of a graph based on the likelihood test of observed and expected ed...
Bei Wang, Jeff M. Phillips, Robert Schreiber, Denn...
139
Voted
ICML
2007
IEEE
16 years 3 months ago
Gradient boosting for kernelized output spaces
A general framework is proposed for gradient boosting in supervised learning problems where the loss function is defined using a kernel over the output space. It extends boosting ...
Florence d'Alché-Buc, Louis Wehenkel, Pierr...
135
Voted
CORR
2006
Springer
127views Education» more  CORR 2006»
15 years 2 months ago
Approximating Rate-Distortion Graphs of Individual Data: Experiments in Lossy Compression and Denoising
Classical rate-distortion theory requires knowledge of an elusive source distribution. Instead, we analyze rate-distortion properties of individual objects using the recently devel...
Steven de Rooij, Paul M. B. Vitányi