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CVPR
2010
IEEE
13 years 6 months ago
Efficient computation of robust low-rank matrix approximations in the presence of missing data using the L1 norm
The calculation of a low-rank approximation of a matrix is a fundamental operation in many computer vision applications. The workhorse of this class of problems has long been the ...
Anders Eriksson, Anton van den Hengel
PAMI
2007
176views more  PAMI 2007»
13 years 7 months ago
Approximate Labeling via Graph Cuts Based on Linear Programming
A new framework is presented for both understanding and developing graph-cut based combinatorial algorithms suitable for the approximate optimization of a very wide class of MRFs ...
Nikos Komodakis, Georgios Tziritas
VLSID
2007
IEEE
94views VLSI» more  VLSID 2007»
14 years 8 months ago
A Reduced Complexity Algorithm for Minimizing N-Detect Tests
? We give a new recursive rounding linear programming (LP) solution to the problem of N-detect test minimzation. This is a polynomialtime solution that closely approximates the exa...
Kalyana R. Kantipudi, Vishwani D. Agrawal
PODC
2006
ACM
14 years 1 months ago
Local approximation schemes for topology control
This paper presents a distributed algorithm for wireless adhoc networks that runs in polylogarithmic number of rounds in the size of the network and constructs a lightweight, line...
Mirela Damian, Saurav Pandit, Sriram V. Pemmaraju
SIAMJO
2010
135views more  SIAMJO 2010»
13 years 6 months ago
On the Complexity of Selecting Disjunctions in Integer Programming
The imposition of general disjunctions of the form “πx ≤ π0 ∨ πx ≥ π0 + 1”, where π, π0 are integer valued, is a fundamental operation in both the branch-and-bound...
Ashutosh Mahajan, Ted K. Ralphs