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ML
2006
ACM
142views Machine Learning» more  ML 2006»
15 years 6 months ago
The max-min hill-climbing Bayesian network structure learning algorithm
We present a new algorithm for Bayesian network structure learning, called Max-Min Hill-Climbing (MMHC). The algorithm combines ideas from local learning, constraint-based, and sea...
Ioannis Tsamardinos, Laura E. Brown, Constantin F....
INFOVIS
2000
IEEE
15 years 10 months ago
Interactive Problem Solving via Algorithm Visualization
COMIND is a tool for conceptual design of industrial products. It helps designers define and evaluate the initial design space by using search algorithms to generate sets of feasi...
Pearl Pu, Denis Lalanne
ICDM
2007
IEEE
132views Data Mining» more  ICDM 2007»
16 years 23 days ago
Error-Aware Density-Based Clustering of Imprecise Measurement Values
Manufacturing process development is under constant pressure to achieve a good yield for stable processes. The development of new technologies, especially in the field of photoma...
Dirk Habich, Peter Benjamin Volk, Wolfgang Lehner,...
KDD
2009
ACM
206views Data Mining» more  KDD 2009»
16 years 7 months ago
Ranking-based clustering of heterogeneous information networks with star network schema
A heterogeneous information network is an information network composed of multiple types of objects. Clustering on such a network may lead to better understanding of both hidden s...
Yizhou Sun, Yintao Yu, Jiawei Han
CHES
2009
Springer
157views Cryptology» more  CHES 2009»
16 years 7 months ago
Differential Cluster Analysis
Abstract. We propose a new technique called Differential Cluster Analysis for side-channel key recovery attacks. This technique uses cluster analysis to detect internal collisions ...
Lejla Batina, Benedikt Gierlichs, Kerstin Lemke-Ru...