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SIAMJO
2010
125views more  SIAMJO 2010»
14 years 6 months ago
Trading Accuracy for Sparsity in Optimization Problems with Sparsity Constraints
We study the problem of minimizing the expected loss of a linear predictor while constraining its sparsity, i.e., bounding the number of features used by the predictor. While the r...
Shai Shalev-Shwartz, Nathan Srebro, Tong Zhang
ANTS
1994
Springer
92views Algorithms» more  ANTS 1994»
15 years 3 months ago
The complexity of greatest common divisor computations
We study the complexity of expressing the greatest common divisor of n positive numbers as a linear combination of the numbers. We prove the NP-completeness of finding an optimal s...
Bohdan S. Majewski, George Havas
ACNS
2011
Springer
254views Cryptology» more  ACNS 2011»
14 years 2 months ago
Linear Analysis of Reduced-Round CubeHash
Abstract. Recent developments in the field of cryptanalysis of hash functions has inspired NIST to announce a competition for selecting a new cryptographic hash function to join t...
Tomer Ashur, Orr Dunkelman
SODA
2010
ACM
216views Algorithms» more  SODA 2010»
15 years 8 months ago
On linear and semidefinite programming relaxations for hypergraph matching
The hypergraph matching problem is to find a largest collection of disjoint hyperedges in a hypergraph. This is a well-studied problem in combinatorial optimization and graph theo...
Yuk Hei Chan, Lap Chi Lau
99
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IPSN
2004
Springer
15 years 4 months ago
Estimation from lossy sensor data: jump linear modeling and Kalman filtering
Due to constraints in cost, power, and communication, losses often arise in large sensor networks. The sensor can be modeled as an output of a linear stochastic system with random...
Alyson K. Fletcher, Sundeep Rangan, Vivek K. Goyal