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» Iterated importance sampling in missing data problems
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RECOMB
2005
Springer
14 years 7 months ago
RIBRA-An Error-Tolerant Algorithm for the NMR Backbone Assignment Problem
We develop an iterative relaxation algorithm, called RIBRA, for NMR protein backbone assignment. RIBRA applies nearest neighbor and weighted maximum independent set algorithms to ...
Kuen-Pin Wu, Jia-Ming Chang, Jun-Bo Chen, Chi-Fon ...
NIPS
2003
13 years 8 months ago
Factorization with Uncertainty and Missing Data: Exploiting Temporal Coherence
The problem of “Structure From Motion” is a central problem in vision: given the 2D locations of certain points we wish to recover the camera motion and the 3D coordinates of ...
Amit Gruber, Yair Weiss
ICML
2009
IEEE
14 years 8 months ago
Importance weighted active learning
We propose an importance weighting framework for actively labeling samples. This technique yields practical yet sound active learning algorithms for general loss functions. Experi...
Alina Beygelzimer, Sanjoy Dasgupta, John Langford
ECCV
2002
Springer
14 years 9 months ago
Linear Multi View Reconstruction with Missing Data
General multi view reconstruction from affine or projective cameras has so far been solved most efficiently using methods of factorizing image data matrices into camera and scene p...
Carsten Rother, Stefan Carlsson
SDM
2010
SIAM
204views Data Mining» more  SDM 2010»
13 years 8 months ago
Scalable Tensor Factorizations with Missing Data
The problem of missing data is ubiquitous in domains such as biomedical signal processing, network traffic analysis, bibliometrics, social network analysis, chemometrics, computer...
Evrim Acar, Daniel M. Dunlavy, Tamara G. Kolda, Mo...