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ICDM
2008
IEEE
230views Data Mining» more  ICDM 2008»
15 years 8 months ago
Evolutionary Clustering by Hierarchical Dirichlet Process with Hidden Markov State
This paper studies evolutionary clustering, which is a recently hot topic with many important applications, noticeably in social network analysis. In this paper, based on the rece...
Tianbing Xu, Zhongfei (Mark) Zhang, Philip S. Yu, ...
CIKM
2009
Springer
15 years 8 months ago
Combining labeled and unlabeled data with word-class distribution learning
We describe a novel simple and highly scalable semi-supervised method called Word-Class Distribution Learning (WCDL), and apply it the task of information extraction (IE) by utili...
Yanjun Qi, Ronan Collobert, Pavel Kuksa, Koray Kav...
NAACL
2007
15 years 2 months ago
Comparing User Simulation Models For Dialog Strategy Learning
This paper explores what kind of user simulation model is suitable for developing a training corpus for using Markov Decision Processes (MDPs) to automatically learn dialog strate...
Hua Ai, Joel R. Tetreault, Diane J. Litman
ICML
1997
IEEE
16 years 2 months ago
Robot Learning From Demonstration
The goal of robot learning from demonstration is to have a robot learn from watching a demonstration of the task to be performed. In our approach to learning from demonstration th...
Christopher G. Atkeson, Stefan Schaal
CVPR
2011
IEEE
14 years 9 months ago
Supervised Hierarchical Pitman-Yor Process for Natural Scene Segmentation
From conventional wisdom and empirical studies of annotated data, it has been shown that visual statistics such as object frequencies and segment sizes follow power law distributi...
Alex Shyr, Trevor Darrell, Michael Jordan, Raquel ...