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ISNN
2011
Springer
12 years 8 months ago
Orthogonal Feature Learning for Time Series Clustering
This paper presents a new method that uses orthogonalized features for time series clustering and classification. To cluster or classify time series data, either original data or...
Xiaozhe Wang, Leo Lopes
CVPR
2007
IEEE
14 years 7 months ago
Segmenting Motions of Different Types by Unsupervised Manifold Clustering
We propose a novel algorithm for segmenting multiple motions of different types from point correspondences in multiple affine or perspective views. Since point trajectories associ...
Alvina Goh, René Vidal
IROS
2009
IEEE
138views Robotics» more  IROS 2009»
14 years 13 days ago
Using eigenposes for lossless periodic human motion imitation
— Programming a humanoid robot to perform an action that takes the robot’s complex dynamics into account is a challenging problem. Traditional approaches typically require high...
Rawichote Chalodhorn, Rajesh P. N. Rao
TSP
2008
151views more  TSP 2008»
13 years 5 months ago
Reduce and Boost: Recovering Arbitrary Sets of Jointly Sparse Vectors
The rapid developing area of compressed sensing suggests that a sparse vector lying in a high dimensional space can be accurately and efficiently recovered from only a small set of...
Moshe Mishali, Yonina C. Eldar
SIGIR
1992
ACM
13 years 9 months ago
Classifying News Stories using Memory Based Reasoning
ct tasks such as extraction of relational information from text [Young] [Jacobs]. We describe a method for classifying news stories using Alternative systems [Biebricher] [Lewis] u...
Brij M. Masand, Gordon Linoff, David L. Waltz