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NIPS
2008
15 years 8 months ago
Covariance Estimation for High Dimensional Data Vectors Using the Sparse Matrix Transform
Covariance estimation for high dimensional vectors is a classically difficult problem in statistical analysis and machine learning. In this paper, we propose a maximum likelihood ...
Guangzhi Cao, Charles A. Bouman
ACL
1998
15 years 7 months ago
Dialogue Act Tagging with Transformation-Based Learning
For the task of recognizing dialogue acts, we are applying the Transformation-Based Learning (TBL) machine learning algorithm. To circumvent a sparse data problem, we extract valu...
Ken Samuel, Sandra Carberry, K. Vijay-Shanker
DAGM
2010
Springer
15 years 7 months ago
3D Object Detection Using a Fast Voxel-Wise Local Spherical Fourier Tensor Transformation
In this paper we present a novel approach for expanding spherical 3D-tensor fields of arbitrary order in terms of a tensor valued local Fourier basis. For an efficient implementati...
Henrik Skibbe, Marco Reisert, Thorsten Schmidt, Kl...
ICASSP
2010
IEEE
15 years 6 months ago
Fast signal analysis and decomposition on graphs using the Sparse Matrix Transform
Recently, the Sparse Matrix Transform (SMT) has been proposed as a tool for estimating the eigen-decomposition of high dimensional data vectors [1]. The SMT approach has two major...
Leonardo R. Bachega, Guangzhi Cao, Charles A. Boum...
CGF
2007
126views more  CGF 2007»
15 years 6 months ago
A Bidirectional Light Field - Hologram Transform
In this paper, we propose a novel framework to represent visual information. Extending the notion of conventional image-based rendering, our framework makes joint use of both ligh...
Remo Ziegler, Simon Bucheli, Lukas Ahrenberg, Marc...