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KDD
2007
ACM
276views Data Mining» more  KDD 2007»
16 years 8 months ago
Nonlinear adaptive distance metric learning for clustering
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...
Jianhui Chen, Zheng Zhao, Jieping Ye, Huan Liu
KDD
2005
ACM
182views Data Mining» more  KDD 2005»
16 years 8 months ago
Making holistic schema matching robust: an ensemble approach
The Web has been rapidly "deepened" by myriad searchable databases online, where data are hidden behind query interfaces. As an essential task toward integrating these m...
Bin He, Kevin Chen-Chuan Chang
CVPR
2006
IEEE
16 years 9 months ago
3D People Tracking with Gaussian Process Dynamical Models
We advocate the use of Gaussian Process Dynamical Models (GPDMs) for learning human pose and motion priors for 3D people tracking. A GPDM provides a lowdimensional embedding of hu...
Raquel Urtasun, David J. Fleet, Pascal Fua
ICASSP
2009
IEEE
16 years 2 months ago
Real-time dynamic MR image reconstruction using Kalman Filtered Compressed Sensing
In recent work, Kalman Filtered Compressed Sensing (KF-CS) was proposed to causally reconstruct time sequences of sparse signals, from a limited number of “incoherent” measure...
Chenlu Qiu, Wei Lu, Namrata Vaswani
GECCO
2007
Springer
163views Optimization» more  GECCO 2007»
16 years 1 months ago
Discovering event evidence amid massive, dynamic datasets
Automated event extraction remains a very difficult challenge requiring information analysts to manually identify key events of interest within massive, dynamic data. Many techniq...
Robert M. Patton, Thomas E. Potok