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» Supervised dimensionality reduction using mixture models
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NIPS
2007
15 years 1 months ago
Random Projections for Manifold Learning
We propose a novel method for linear dimensionality reduction of manifold modeled data. First, we show that with a small number M of random projections of sample points in RN belo...
Chinmay Hegde, Michael B. Wakin, Richard G. Barani...
CVPR
2007
IEEE
16 years 1 months ago
Artificial Complex Cells via the Tropical Semiring
The seminal work of Hubel and Wiesel [14] and the vast amount of work that followed it prove that hierarchies of increasingly complex cells play a central role in cortical computa...
Lior Wolf, Moshe Guttmann
ICML
2000
IEEE
16 years 17 days ago
On-line Learning for Humanoid Robot Systems
Humanoid robots are high-dimensional movement systems for which analytical system identification and control methods are insufficient due to unknown nonlinearities in the system s...
Gaurav Tevatia, Jörg Conradt, Sethu Vijayakum...
ICML
2009
IEEE
16 years 17 days ago
Matrix updates for perceptron training of continuous density hidden Markov models
In this paper, we investigate a simple, mistakedriven learning algorithm for discriminative training of continuous density hidden Markov models (CD-HMMs). Most CD-HMMs for automat...
Chih-Chieh Cheng, Fei Sha, Lawrence K. Saul
TASLP
2010
101views more  TASLP 2010»
14 years 6 months ago
Gaussian Model-Based Multichannel Speech Presence Probability
The knowledge of the target speech presence probability in a mixture of signals captured by a speech communication system is of paramount importance in several applications includi...
Mehrez Souden, Jingdong Chen, Jacob Benesty, Sofi&...