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ICML
1996
IEEE
16 years 2 months ago
Discretizing Continuous Attributes While Learning Bayesian Networks
We introduce a method for learning Bayesian networks that handles the discretization of continuous variables as an integral part of the learning process. The main ingredient in th...
Moisés Goldszmidt, Nir Friedman
SIGOPS
2008
146views more  SIGOPS 2008»
15 years 1 months ago
Vigilant: out-of-band detection of failures in virtual machines
What do our computer systems do all day? How do we make sure they continue doing it when failures occur? Traditional approaches to answering these questions often involve inband m...
Dan Pelleg, Muli Ben-Yehuda, Richard Harper, Lisa ...
ICML
2008
IEEE
16 years 2 months ago
Classification using discriminative restricted Boltzmann machines
Recently, many applications for Restricted Boltzmann Machines (RBMs) have been developed for a large variety of learning problems. However, RBMs are usually used as feature extrac...
Hugo Larochelle, Yoshua Bengio
KDD
1997
ACM
184views Data Mining» more  KDD 1997»
15 years 6 months ago
JAM: Java Agents for Meta-Learning over Distributed Databases
In this paper, we describe the JAM system, a distributed, scalable and portable agent-based data mining system that employs a general approach to scaling data mining applications ...
Salvatore J. Stolfo, Andreas L. Prodromidis, Shell...
ICMLA
2009
14 years 11 months ago
Alive on Back-feed Culprit Identification via Machine Learning
We describe an application of machine learning techniques toward the problem of predicting which network protector switch is the cause of an Alive on Back-Feed (ABF) event in the ...
Bert C. Huang, Ansaf Salleb-Aouissi, Philip Gross