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» Evaluating learning algorithms and classifiers
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103
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CIKM
1997
Springer
15 years 4 months ago
Learning Belief Networks from Data: An Information Theory Based Approach
This paper presents an efficient algorithm for learning Bayesian belief networks from databases. The algorithm takes a database as input and constructs the belief network structur...
Jie Cheng, David A. Bell, Weiru Liu
122
Voted
NIPS
2004
15 years 1 months ago
Semi-supervised Learning on Directed Graphs
Given a directed graph in which some of the nodes are labeled, we investigate the question of how to exploit the link structure of the graph to infer the labels of the remaining u...
Dengyong Zhou, Bernhard Schölkopf, Thomas Hof...
104
Voted
NIPS
2000
15 years 1 months ago
Incremental and Decremental Support Vector Machine Learning
An on-line recursive algorithm for training support vector machines, one vector at a time, is presented. Adiabatic increments retain the KuhnTucker conditions on all previously se...
Gert Cauwenberghs, Tomaso Poggio
CCS
2009
ACM
15 years 7 months ago
Active learning for network intrusion detection
Anomaly detection for network intrusion detection is usually considered an unsupervised task. Prominent techniques, such as one-class support vector machines, learn a hypersphere ...
Nico Görnitz, Marius Kloft, Konrad Rieck, Ulf...
123
Voted
ICDE
2011
IEEE
258views Database» more  ICDE 2011»
14 years 4 months ago
SystemML: Declarative machine learning on MapReduce
Abstract—MapReduce is emerging as a generic parallel programming paradigm for large clusters of machines. This trend combined with the growing need to run machine learning (ML) a...
Amol Ghoting, Rajasekar Krishnamurthy, Edwin P. D....