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» Evaluating algorithms that learn from data streams
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ESWS
2008
Springer
15 years 8 months ago
Instance Based Clustering of Semantic Web Resources
Abstract. The original Semantic Web vision was explicit in the need for intelligent autonomous agents that would represent users and help them navigate the Semantic Web. We argue t...
Gunnar Aastrand Grimnes, Peter Edwards, Alun D. Pr...
COLING
2010
15 years 1 months ago
Semi-supervised Semantic Pattern Discovery with Guidance from Unsupervised Pattern Clusters
We present a simple algorithm for clustering semantic patterns based on distributional similarity and use cluster memberships to guide semi-supervised pattern discovery. We apply ...
Ang Sun, Ralph Grishman
ICMCS
2006
IEEE
117views Multimedia» more  ICMCS 2006»
16 years 14 days ago
DIBR-Based 3D Videos using Non Video Rate Range Image Stream
The fundamental assumption of 3D videos using depth-imagebased rendering is the full availability of range images at video rate. In this work we alleviate this hard demand and ass...
Xiaoyi Jiang, Martin Lambers
BIBM
2010
IEEE
139views Bioinformatics» more  BIBM 2010»
15 years 3 months ago
Scalable, updatable predictive models for sequence data
The emergence of data rich domains has led to an exponential growth in the size and number of data repositories, offering exciting opportunities to learn from the data using machin...
Neeraj Koul, Ngot Bui, Vasant Honavar
KDD
2002
ACM
147views Data Mining» more  KDD 2002»
16 years 6 months ago
Sequential cost-sensitive decision making with reinforcement learning
Recently, there has been increasing interest in the issues of cost-sensitive learning and decision making in a variety of applications of data mining. A number of approaches have ...
Edwin P. D. Pednault, Naoki Abe, Bianca Zadrozny