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ICDM
2010
IEEE
142views Data Mining» more  ICDM 2010»
13 years 6 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
METMBS
2003
255views Mathematics» more  METMBS 2003»
13 years 9 months ago
Causal Explorer: A Causal Probabilistic Network Learning Toolkit for Biomedical Discovery
Causal Probabilistic Networks (CPNs), (a.k.a. Bayesian Networks, or Belief Networks) are well-established representations in biomedical applications such as decision support system...
Constantin F. Aliferis, Ioannis Tsamardinos, Alexa...

Book
519views
15 years 7 months ago
Information Theory, Inference, and Learning Algorithms
This book is aimed at senior undergraduates and graduate students in Engineering, Science, Mathematics, and Computing. It expects familiarity with calculus, probability theory, and...
David J. C. MacKay
KDD
2010
ACM
224views Data Mining» more  KDD 2010»
13 years 12 months ago
Multi-label learning by exploiting label dependency
In multi-label learning, each training example is associated with a set of labels and the task is to predict the proper label set for the unseen example. Due to the tremendous (ex...
Min-Ling Zhang, Kun Zhang
ICDCSW
2006
IEEE
14 years 2 months ago
Improve Searching by Reinforcement Learning in Unstructured P2Ps
— Existing searching schemes in unstructured P2Ps can be categorized as either blind or informed. The quality of query results in blind schemes is low. Informed schemes use simpl...
Xiuqi Li, Jie Wu