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» Structured metric learning for high dimensional problems
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CVPR
2008
IEEE
14 years 9 months ago
Approximate earth mover's distance in linear time
The earth mover's distance (EMD) [16] is an important perceptually meaningful metric for comparing histograms, but it suffers from high (O(N3 log N)) computational complexity...
Sameer Shirdhonkar, David W. Jacobs
PKDD
2005
Springer
101views Data Mining» more  PKDD 2005»
14 years 1 months ago
A Random Method for Quantifying Changing Distributions in Data Streams
In applications such as fraud and intrusion detection, it is of great interest to measure the evolving trends in the data. We consider the problem of quantifying changes between tw...
Haixun Wang, Jian Pei
JMLR
2010
119views more  JMLR 2010»
13 years 2 months ago
The Group Dantzig Selector
We introduce a new method -- the group Dantzig selector -- for high dimensional sparse regression with group structure, which has a convincing theory about why utilizing the group...
Han Liu, Jian Zhang 0003, Xiaoye Jiang, Jun Liu
AAAI
2008
13 years 10 months ago
Structure Learning on Large Scale Common Sense Statistical Models of Human State
Research has shown promise in the design of large scale common sense probabilistic models to infer human state from environmental sensor data. These models have made use of mined ...
William Pentney, Matthai Philipose, Jeff A. Bilmes
ICML
2000
IEEE
14 years 8 months 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...