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SIAMJO
2010
125views more  SIAMJO 2010»
14 years 7 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 4 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 4 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 10 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
113
Voted
IPSN
2004
Springer
15 years 6 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