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» Evaluating algorithms that learn from data streams
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KDD
2010
ACM
233views Data Mining» more  KDD 2010»
15 years 11 months ago
Evolutionary hierarchical dirichlet processes for multiple correlated time-varying corpora
Mining cluster evolution from multiple correlated time-varying text corpora is important in exploratory text analytics. In this paper, we propose an approach called evolutionary h...
Jianwen Zhang, Yangqiu Song, Changshui Zhang, Shix...
224
Voted
CVPR
2006
IEEE
16 years 9 months ago
BoostMotion: Boosting a Discriminative Similarity Function for Motion Estimation
Motion estimation for applications where appearance undergoes complex changes is challenging due to lack of an appropriate similarity function. In this paper, we propose to learn ...
Shaohua Kevin Zhou, Bogdan Georgescu, Dorin Comani...
215
Voted
BMCBI
2004
181views more  BMCBI 2004»
15 years 7 months ago
Iterative class discovery and feature selection using Minimal Spanning Trees
Background: Clustering is one of the most commonly used methods for discovering hidden structure in microarray gene expression data. Most current methods for clustering samples ar...
Sudhir Varma, Richard Simon
225
Voted
ECCV
2002
Springer
16 years 9 months ago
SoftPOSIT: Simultaneous Pose and Correspondence Determination
The problem of pose estimation arises in many areas of computer vision, including object recognition, object tracking, site inspection and updating, and autonomous navigation when...
Philip David, Daniel DeMenthon, Ramani Duraiswami,...
CIKM
2008
Springer
15 years 9 months ago
Trada: tree based ranking function adaptation
Machine Learned Ranking approaches have shown successes in web search engines. With the increasing demands on developing effective ranking functions for different search domains, ...
Keke Chen, Rongqing Lu, C. K. Wong, Gordon Sun, La...