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ICASSP
2011
IEEE
12 years 11 months ago
Low-rank matrix completion by variational sparse Bayesian learning
There has been a significant interest in the recovery of low-rank matrices from an incomplete of measurements, due to both theoretical and practical developments demonstrating th...
S. Derin Babacan, Martin Luessi, Rafael Molina, Ag...
IPL
2011
91views more  IPL 2011»
13 years 2 months ago
A note on improving the performance of approximation algorithms for radiation therapy
The segment minimization problem consists of representing an integer matrix as the sum of the fewest number of integer matrices each of which have the property that the non-zeroes...
Therese C. Biedl, Stephane Durocher, Holger H. Hoo...
ICASSP
2011
IEEE
12 years 11 months ago
Co-clustering as multilinear decomposition with sparse latent factors
The K-means clustering problem seeks to partition the columns of a data matrix in subsets, such that columns in the same subset are ‘close’ to each other. The co-clustering pr...
Evangelos E. Papalexakis, Nicholas D. Sidiropoulos
ESA
2007
Springer
150views Algorithms» more  ESA 2007»
14 years 1 months ago
On the Complexity of Sequential Rectangle Placement in IEEE 802.16/WiMAX Systems
We study the problem of scheduling transmissions on the downlink of IEEE 802.16/WiMAX systems that use the OFDMA technology. These transmissions are scheduled using a matrix whose...
Amos Israeli, Dror Rawitz, Oran Sharon
STOC
2012
ACM
221views Algorithms» more  STOC 2012»
11 years 10 months ago
From query complexity to computational complexity
We consider submodular optimization problems, and provide a general way of translating oracle inapproximability results arising from the symmetry gap technique to computational co...
Shahar Dobzinski, Jan Vondrák