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» Randomizing Reductions of Search Problems
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CRV
2011
IEEE
352views Robotics» more  CRV 2011»
12 years 7 months ago
Conformative Filter: A Probabilistic Framework for Localization in Reduced Space
— Algorithmic problem reduction is a fundamental approach to problem solving in many fields, including robotics. To solve a problem using this scheme, we must reduce the problem...
Chatavut Viriyasuthee, Gregory Dudek
GECCO
2003
Springer
14 years 1 months ago
Selection in the Presence of Noise
For noisy optimization problems, there is generally a trade-off between the effort spent to reduce the noise (in order to allow the optimization algorithm to run properly), and t...
Jürgen Branke, Christian Schmidt 0002
OL
2007
121views more  OL 2007»
13 years 7 months ago
Global optimization by continuous grasp
We introduce a novel global optimization method called Continuous GRASP (C-GRASP) which extends Feo and Resende’s greedy randomized adaptive search procedure (GRASP) from the dom...
Michael J. Hirsch, Cláudio Nogueira de Mene...
WWW
2005
ACM
14 years 8 months ago
Sampling search-engine results
We consider the problem of efficiently sampling Web search engine query results. In turn, using a small random sample instead of the full set of results leads to efficient approxi...
Aris Anagnostopoulos, Andrei Z. Broder, David Carm...
SIGECOM
2010
ACM
164views ECommerce» more  SIGECOM 2010»
14 years 22 days ago
Truthful mechanisms with implicit payment computation
It is widely believed that computing payments needed to induce truthful bidding is somehow harder than simply computing the allocation. We show that the opposite is true for singl...
Moshe Babaioff, Robert D. Kleinberg, Aleksandrs Sl...