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ICDM
2006
IEEE
137views Data Mining» more  ICDM 2006»
14 years 4 months ago
Mining Complex Time-Series Data by Learning Markovian Models
In this paper, we propose a novel and general approach for time-series data mining. As an alternative to traditional ways of designing specific algorithm to mine certain kind of ...
Yi Wang, Lizhu Zhou, Jianhua Feng, Jianyong Wang, ...
HCI
2009
13 years 8 months ago
An Open Source Framework for Real-Time, Incremental, Static and Dynamic Hand Gesture Learning and Recognition
Real-time, static and dynamic hand gesture learning and recognition makes it possible to have computers recognize hand gestures naturally. This creates endless possibilities in the...
Todd C. Alexander, Hassan S. Ahmed, Georgios C. An...
NIPS
2003
13 years 11 months ago
Learning Near-Pareto-Optimal Conventions in Polynomial Time
We study how to learn to play a Pareto-optimal strict Nash equilibrium when there exist multiple equilibria and agents may have different preferences among the equilibria. We focu...
Xiao Feng Wang, Tuomas Sandholm
ALT
2003
Springer
14 years 7 months ago
Learning a Subclass of Regular Patterns in Polynomial Time
An algorithm for learning a subclass of erasing regular pattern languages is presented. On extended regular pattern languages generated by patterns π of the form x0α1x1 . . . α...
John Case, Sanjay Jain, Rüdiger Reischuk, Fra...
SDM
2011
SIAM
256views Data Mining» more  SDM 2011»
13 years 1 months ago
Temporal Structure Learning for Clustering Massive Data Streams in Real-Time
This paper describes one of the first attempts to model the temporal structure of massive data streams in real-time using data stream clustering. Recently, many data stream clust...
Michael Hahsler, Margaret H. Dunham