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KDD
2006
ACM
153views Data Mining» more  KDD 2006»
16 years 7 months ago
Spatial scan statistics: approximations and performance study
Spatial scan statistics are used to determine hotspots in spatial data, and are widely used in epidemiology and biosurveillance. In recent years, there has been much effort invest...
Deepak Agarwal, Andrew McGregor, Jeff M. Phillips,...
INFOCOM
2012
IEEE
13 years 9 months ago
Approximately optimal adaptive learning in opportunistic spectrum access
—In this paper we develop an adaptive learning algorithm which is approximately optimal for an opportunistic spectrum access (OSA) problem with polynomial complexity. In this OSA...
Cem Tekin, Mingyan Liu
FOCS
1995
IEEE
15 years 10 months ago
Free Bits, PCPs and Non-Approximability - Towards Tight Results
This paper continues the investigation of the connection between probabilistically checkable proofs PCPs the approximability of NP-optimization problems. The emphasis is on prov...
Mihir Bellare, Oded Goldreich, Madhu Sudan
CORR
2008
Springer
96views Education» more  CORR 2008»
15 years 6 months ago
Improved Approximations for Multiprocessor Scheduling Under Uncertainty
This paper presents improved approximation algorithms for the problem of multiprocessor scheduling under uncertainty (SUU), in which the execution of each job may fail probabilist...
Christopher Y. Crutchfield, Zoran Dzunic, Jeremy T...
CORR
2012
Springer
170views Education» more  CORR 2012»
14 years 2 months ago
What Cannot be Learned with Bethe Approximations
We address the problem of learning the parameters in graphical models when inference is intractable. A common strategy in this case is to replace the partition function with its B...
Uri Heinemann, Amir Globerson