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» Hashing Methods for Temporal Data
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ICML
2009
IEEE
15 years 10 months ago
Learning linear dynamical systems without sequence information
Virtually all methods of learning dynamic systems from data start from the same basic assumption: that the learning algorithm will be provided with a sequence, or trajectory, of d...
Tzu-Kuo Huang, Jeff Schneider
ICRA
2000
IEEE
129views Robotics» more  ICRA 2000»
15 years 7 months ago
Data Association for Mobile Robot Navigation: A Graph Theoretic Approach
Data association is the process of relating features observed in the environment to features viewed previously or to features in a map. Correct feature association is essential fo...
Tim Bailey, Eduardo Mario Nebot, Julio Rosenblatt,...
KES
2010
Springer
15 years 1 months ago
Extracting Principal Components from Pseudo-random Data by Using Random Matrix Theory
We develop a methodology to grasp temporal trend in a stock market that changes year to year, or sometimes within a year depending on numerous factors. For this purpose, we employ ...
Mieko Tanaka-Yamawaki
ISBI
2008
IEEE
16 years 3 months ago
Segmentation of the evolving left ventricle by learning the dynamics
We propose a method for recursive segmentation of the left ventricle (LV) across a temporal sequence of magnetic resonance (MR) images. The approach involves a technique for learn...
Walter Sun, Müjdat Çetin, Raymond Chan...
140
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JIIS
2002
114views more  JIIS 2002»
15 years 2 months ago
A Dynamic Probabilistic Model to Visualise Topic Evolution in Text Streams
Abstract. We propose a novel probabilistic method, based on latent variable models, for unsupervised topographic visualisation of dynamically evolving, coherent textual information...
Ata Kabán, Mark Girolami