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» Telling cause from effect based on high-dimensional observat...
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ICML
2010
IEEE
13 years 6 months ago
Telling cause from effect based on high-dimensional observations
Dominik Janzing, Patrik O. Hoyer, Bernhard Sch&oum...
INFOVIS
2003
IEEE
13 years 10 months ago
Interactive Hierarchical Dimension Ordering, Spacing and Filtering for Exploration of High Dimensional Datasets
Large numbers of dimensions not only cause clutter in multidimensional visualizations, but also make it difficult for users to navigate the data space. Effective dimension manage...
Jing Yang, Wei Peng, Matthew O. Ward, Elke A. Rund...
ACCV
2007
Springer
13 years 11 months ago
Interpolation Between Eigenspaces Using Rotation in Multiple Dimensions
We propose a method for interpolation between eigenspaces. Techniques that represent observed patterns as multivariate normal distribution have actively been developed to make it r...
Tomokazu Takahashi, Lina, Ichiro Ide, Yoshito Meka...
ECCV
2006
Springer
13 years 6 months ago
Recognition and Segmentation of 3-D Human Action Using HMM and Multi-class AdaBoost
Our goal is to automatically segment and recognize basic human actions, such as stand, walk and wave hands, from a sequence of joint positions or pose angles. Such recognition is d...
Fengjun Lv, Ramakant Nevatia
WISE
2002
Springer
13 years 9 months ago
A Unified Framework for Clustering Heterogeneous Web Objects
In this paper, we introduce a novel framework for clustering web data which is often heterogeneous in nature. As most existing methods often integrate heterogeneous data into a un...
Hua-Jun Zeng, Zheng Chen, Wei-Ying Ma