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SDM
2012
SIAM
355views Data Mining» more  SDM 2012»
13 years 4 months ago
Granger Causality Analysis in Irregular Time Series
Learning temporal causal structures between time series is one of the key tools for analyzing time series data. In many real-world applications, we are confronted with Irregular T...
Mohammad Taha Bahadori, Yan Liu
CIDM
2007
IEEE
15 years 5 months ago
Mining the Students' Learning Interest in Browsing Web-Streaming Lectures
Web-Streaming lectures overcome the space and time barriers between learning and teaching, but bring higher requirements on the learning feedback of students when they browse lectu...
Long Wang 0002, Christoph Meinel
IJON
2010
120views more  IJON 2010»
15 years 11 days ago
Semi-supervised learning with varifold Laplacians
This paper presents varifold learning, a learning framework based on the mathematical concept of varifolds. Different from manifold based methods, our varifold learning framework ...
Lei Ding, Peibiao Zhao
WECWIS
2002
IEEE
112views ECommerce» more  WECWIS 2002»
15 years 6 months ago
Separating Business Process from User Interaction Utilizing Process-Aware XSLT Style-Sheets
In the web context, it is difficult to disentangle presentation from process logic, and sometimes even data is not separate from the presentation. Consequently, it becomes to de...
Karl Aberer, Anwitaman Datta, Zoran Despotovic
ICDM
2009
IEEE
141views Data Mining» more  ICDM 2009»
15 years 8 months ago
Discovering Excitatory Networks from Discrete Event Streams with Applications to Neuronal Spike Train Analysis
—Mining temporal network models from discrete event streams is an important problem with applications in computational neuroscience, physical plant diagnostics, and human-compute...
Debprakash Patnaik, Srivatsan Laxman, Naren Ramakr...