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STOC
1997
ACM
125views Algorithms» more  STOC 1997»
15 years 10 months ago
An Interruptible Algorithm for Perfect Sampling via Markov Chains
For a large class of examples arising in statistical physics known as attractive spin systems (e.g., the Ising model), one seeks to sample from a probability distribution π on an...
James Allen Fill
IPPS
1996
IEEE
15 years 10 months ago
Practical Parallel Algorithms for Dynamic Data Redistribution, Median Finding, and Selection
A common statistical problem is that of nding the median element in a set of data. This paper presents a fastand portable parallel algorithm for nding the median given a set of el...
David A. Bader, Joseph JáJá
KDD
2010
ACM
274views Data Mining» more  KDD 2010»
15 years 10 months ago
Grafting-light: fast, incremental feature selection and structure learning of Markov random fields
Feature selection is an important task in order to achieve better generalizability in high dimensional learning, and structure learning of Markov random fields (MRFs) can automat...
Jun Zhu, Ni Lao, Eric P. Xing
KDD
2010
ACM
272views Data Mining» more  KDD 2010»
15 years 10 months ago
Beyond heuristics: learning to classify vulnerabilities and predict exploits
The security demands on modern system administration are enormous and getting worse. Chief among these demands, administrators must monitor the continual ongoing disclosure of sof...
Mehran Bozorgi, Lawrence K. Saul, Stefan Savage, G...
KDD
2010
ACM
253views Data Mining» more  KDD 2010»
15 years 10 months ago
Mining periodic behaviors for moving objects
Periodicity is a frequently happening phenomenon for moving objects. Finding periodic behaviors is essential to understanding object movements. However, periodic behaviors could b...
Zhenhui Li, Bolin Ding, Jiawei Han, Roland Kays, P...
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