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» Efficient Discovery of Confounders in Large Data Sets
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ESA
2010
Springer
183views Algorithms» more  ESA 2010»
15 years 7 months ago
Spatio-temporal Range Searching over Compressed Kinetic Sensor Data
As sensor networks increase in size and number, efficient techniques are required to process the very large data sets that they generate. Frequently, sensor networks monitor object...
Sorelle A. Friedler, David M. Mount
DEXA
2008
Springer
117views Database» more  DEXA 2008»
15 years 8 months ago
Space-Partitioning-Based Bulk-Loading for the NSP-Tree in Non-ordered Discrete Data Spaces
Properly-designed bulk-loading techniques are more efficient than the conventional tuple-loading method in constructing a multidimensional index tree for a large data set. Although...
Gang Qian, Hyun-Jeong Seok, Qiang Zhu, Sakti Prama...
ECCV
2008
Springer
16 years 8 months ago
Quick Shift and Kernel Methods for Mode Seeking
We show that the complexity of the recently introduced medoid-shift algorithm in clustering N points is O(N2 ), with a small constant, if the underlying distance is Euclidean. This...
Andrea Vedaldi, Stefano Soatto
ICML
2007
IEEE
16 years 7 months ago
Piecewise pseudolikelihood for efficient training of conditional random fields
Discriminative training of graphical models can be expensive if the variables have large cardinality, even if the graphical structure is tractable. In such cases, pseudolikelihood...
Charles A. Sutton, Andrew McCallum
CVPR
2005
IEEE
16 years 8 months ago
Discriminative Learning of Markov Random Fields for Segmentation of 3D Scan Data
We address the problem of segmenting 3D scan data into objects or object classes. Our segmentation framework is based on a subclass of Markov Random Fields (MRFs) which support ef...
Dragomir Anguelov, Benjamin Taskar, Vassil Chatalb...