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ICDM
2010
IEEE
142views Data Mining» more  ICDM 2010»
15 years 4 months ago
Causal Discovery from Streaming Features
In this paper, we study a new research problem of causal discovery from streaming features. A unique characteristic of streaming features is that not all features can be available ...
Kui Yu, Xindong Wu, Hao Wang, Wei Ding
ICDM
2010
IEEE
127views Data Mining» more  ICDM 2010»
15 years 4 months ago
Learning Markov Network Structure with Decision Trees
Traditional Markov network structure learning algorithms perform a search for globally useful features. However, these algorithms are often slow and prone to finding local optima d...
Daniel Lowd, Jesse Davis
ICDM
2010
IEEE
186views Data Mining» more  ICDM 2010»
15 years 4 months ago
MoodCast: Emotion Prediction via Dynamic Continuous Factor Graph Model
Human emotion is one important underlying force affecting and affected by the dynamics of social networks. An interesting question is "can we predict a person's mood base...
Yuan Zhang, Jie Tang, Jimeng Sun, Yiran Chen, Jing...
ICDM
2010
IEEE
150views Data Mining» more  ICDM 2010»
15 years 4 months ago
Detecting Novel Discrepancies in Communication Networks
Abstract--We address the problem of detecting characteristic patterns in communication networks. We introduce a scalable approach based on set-system discrepancy. By implicitly lab...
James Abello, Tina Eliassi-Rad, Nishchal Devanur
ICDM
2010
IEEE
167views Data Mining» more  ICDM 2010»
15 years 4 months ago
Averaged Stochastic Gradient Descent with Feedback: An Accurate, Robust, and Fast Training Method
On large datasets, the popular training approach has been stochastic gradient descent (SGD). This paper proposes a modification of SGD, called averaged SGD with feedback (ASF), tha...
Xu Sun, Hisashi Kashima, Takuya Matsuzaki, Naonori...
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