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ICCV
2001
IEEE
14 years 9 months ago
Image Segmentation by Data Driven Markov Chain Monte Carlo
?This paper presents a computational paradigm called Data-Driven Markov Chain Monte Carlo (DDMCMC) for image segmentation in the Bayesian statistical framework. The paper contribut...
Zhuowen Tu, Song Chun Zhu, Heung-Yeung Shum
KDD
2009
ACM
192views Data Mining» more  KDD 2009»
14 years 2 months ago
Primal sparse Max-margin Markov networks
Max-margin Markov networks (M3 N) have shown great promise in structured prediction and relational learning. Due to the KKT conditions, the M3 N enjoys dual sparsity. However, the...
Jun Zhu, Eric P. Xing, Bo Zhang
ICDM
2009
IEEE
198views Data Mining» more  ICDM 2009»
14 years 2 months ago
Information Extraction for Clinical Data Mining: A Mammography Case Study
Abstract—Breast cancer is the leading cause of cancer mortality in women between the ages of 15 and 54. During mammography screening, radiologists use a strict lexicon (BI-RADS) ...
Houssam Nassif, Ryan Woods, Elizabeth S. Burnside,...
IMC
2006
ACM
14 years 1 months ago
Semi-automated discovery of application session structure
While the problem of analyzing network traffic at the granularity of individual connections has seen considerable previous work and tool development, understanding traffic at a ...
Jayanthkumar Kannan, Jaeyeon Jung, Vern Paxson, Ca...
DASFAA
2005
IEEE
157views Database» more  DASFAA 2005»
14 years 1 months ago
Adaptively Detecting Aggregation Bursts in Data Streams
Finding bursts in data streams is attracting much attention in research community due to its broad applications. Existing burst detection methods suffer the problems that 1) the p...
Aoying Zhou, Shouke Qin, Weining Qian