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NIPS
2008
15 years 9 months ago
On the Complexity of Linear Prediction: Risk Bounds, Margin Bounds, and Regularization
This work characterizes the generalization ability of algorithms whose predictions are linear in the input vector. To this end, we provide sharp bounds for Rademacher and Gaussian...
Sham M. Kakade, Karthik Sridharan, Ambuj Tewari
IJCGA
2010
155views more  IJCGA 2010»
15 years 6 months ago
Competitive Complexity of Mobile Robot on-Line Motion Planning Problems
This paper is concerned with on-line problems where a mobile robot of size D has to achieve a task in an unknown planar environment whose geometry is acquired by the robot during ...
Yoav Gabriely, Elon Rimon
DISOPT
2011
210views Education» more  DISOPT 2011»
15 years 2 months ago
The parameterized complexity of k-flip local search for SAT and MAX SAT
SAT and MAX SAT are among the most prominent problems for which local search algorithms have been successfully applied. A fundamental task for such an algorithm is to increase the...
Stefan Szeider
MP
2011
15 years 2 months ago
Smoothed analysis of condition numbers and complexity implications for linear programming
We perform a smoothed analysis of Renegar’s condition number for linear programming by analyzing the distribution of the distance to ill-posedness of a linear program subject to...
John Dunagan, Daniel A. Spielman, Shang-Hua Teng
165
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CIE
2008
Springer
15 years 9 months ago
Succinct NP Proofs from an Extractability Assumption
Abstract We prove, using a non-standard complexity assumption, that any language in NP has a 1-round (that is, the verifier sends a message to the prover, and the prover sends a me...
Giovanni Di Crescenzo, Helger Lipmaa