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ICDM
2007
IEEE
129views Data Mining» more  ICDM 2007»
8 years 9 months ago
Feature Selection for Nonlinear Kernel Support Vector Machines
An easily implementable mixed-integer algorithm is proposed that generates a nonlinear kernel support vector machine (SVM) classifier with reduced input space features. A single ...
Olvi L. Mangasarian, Gang Kou
ICDM
2007
IEEE
157views Data Mining» more  ICDM 2007»
8 years 9 months ago
Training Conditional Random Fields by Periodic Step Size Adaptation for Large-Scale Text Mining
For applications with consecutive incoming training examples, on-line learning has the potential to achieve a likelihood as high as off-line learning without scanning all availabl...
Han-Shen Huang, Yu-Ming Chang, Chun-Nan Hsu
ICDM
2007
IEEE
140views Data Mining» more  ICDM 2007»
8 years 11 months ago
Sequential Change Detection on Data Streams
Model-based declarative queries are becoming an attractive paradigm for interacting with many data stream applications. This has led to the development of techniques to accurately...
S. Muthukrishnan, Eric van den Berg, Yihua Wu
ICDM
2007
IEEE
248views Data Mining» more  ICDM 2007»
8 years 11 months ago
Adapting SVM Classifiers to Data with Shifted Distributions
Many data mining applications can benefit from adapting existing classifiers to new data with shifted distributions. In this paper, we present Adaptive Support Vector Machine (Ada...
Jun Yang 0003, Rong Yan, Alexander G. Hauptmann
ICDM
2007
IEEE
176views Data Mining» more  ICDM 2007»
8 years 11 months ago
A Compact Representation of Spatio-Temporal Data
As technology advances we encounter more available data on moving objects, which can be mined to our benefit. In order to efficiently mine this large amount of data we propose an ...
Sigal Elnekave, Mark Last, Oded Maimon
ICDM
2007
IEEE
151views Data Mining» more  ICDM 2007»
8 years 11 months ago
Combining Collective Classification and Link Prediction
The problems of object classification (labeling the nodes of a graph) and link prediction (predicting the links in a graph) have been largely studied independently. Commonly, obje...
Mustafa Bilgic, Galileo Namata, Lise Getoor
ICDM
2007
IEEE
162views Data Mining» more  ICDM 2007»
8 years 11 months ago
Exploiting Network Structure for Active Inference in Collective Classification
Active inference seeks to maximize classification performance while minimizing the amount of data that must be labeled ex ante. This task is particularly relevant in the context o...
Matthew J. Rattigan, Marc Maier, David Jensen, Bin...
ICDM
2007
IEEE
131views Data Mining» more  ICDM 2007»
8 years 11 months ago
Predicting and Optimizing Classifier Utility with the Power Law
When data collection is costly and/or takes a significant amount of time, an early prediction of the classifier performance is extremely important for the design of the data minin...
Mark Last
ICDM
2007
IEEE
301views Data Mining» more  ICDM 2007»
8 years 11 months ago
Stream Event Detection: A Unified Framework for Mining Outlier, Change and Burst Simultaneously over Data Stream
Event detection is one of the most important issues of event processing system, especially Complex Event Processing (CEP). Outlier event, change event and burst event are three ty...
Zhijian Yuan, Kai Du, Yan Jia, Jiajia Miao
ICDM
2007
IEEE
156views Data Mining» more  ICDM 2007»
8 years 11 months ago
Computing Correlation Anomaly Scores Using Stochastic Nearest Neighbors
This paper addresses the task of change analysis of correlated multi-sensor systems. The goal of change analysis is to compute the anomaly score of each sensor when we know that t...
Tsuyoshi Idé, Spiros Papadimitriou, Michail...
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