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» Constrained Subspace Modelling
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NIPS
2008
13 years 9 months ago
Diffeomorphic Dimensionality Reduction
This paper introduces a new approach to constructing meaningful lower dimensional representations of sets of data points. We argue that constraining the mapping between the high a...
Christian Walder, Bernhard Schölkopf
ICCV
2007
IEEE
14 years 9 months ago
Robust Visual Tracking Based on Incremental Tensor Subspace Learning
Most existing subspace analysis-based tracking algorithms utilize a flattened vector to represent a target, resulting in a high dimensional data learning problem. Recently, subspa...
Xi Li, Weiming Hu, Zhongfei Zhang, Xiaoqin Zhang, ...
DAGSTUHL
2007
13 years 9 months ago
Subspace outlier mining in large multimedia databases
Abstract. Increasingly large multimedia databases in life sciences, ecommerce, or monitoring applications cannot be browsed manually, but require automatic knowledge discovery in d...
Ira Assent, Ralph Krieger, Emmanuel Müller, T...
ICASSP
2010
IEEE
13 years 7 months ago
Subspace Gaussian Mixture Models for speech recognition
We describe an acoustic modeling approach in which all phonetic states share a common Gaussian Mixture Model structure, and the means and mixture weights vary in a subspace of the...
Daniel Povey, Lukas Burget, Mohit Agarwal, Pinar A...
BMVC
2000
13 years 9 months ago
Probabilistic PCA and ICA Subspace Mixture Models for Image Segmentation
High-dimensional data, such as images represented as points in the space spanned by their pixel values, can often be described in a significantly smaller number of dimensions than...
Dick de Ridder, Josef Kittler, Robert P. W. Duin