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APPROX
2005
Springer
111views Algorithms» more  APPROX 2005»
15 years 3 months ago
Sampling Bounds for Stochastic Optimization
A large class of stochastic optimization problems can be modeled as minimizing an objective function f that depends on a choice of a vector x ∈ X, as well as on a random external...
Moses Charikar, Chandra Chekuri, Martin Pál
UAI
1997
14 years 11 months ago
A Scheme for Approximating Probabilistic Inference
This paper describes a class ofprobabilistic approximation algorithms based on bucket elimination which o er adjustable levels of accuracy ande ciency. We analyzethe approximation...
Rina Dechter, Irina Rish
SIGMOD
2011
ACM
158views Database» more  SIGMOD 2011»
14 years 19 days ago
Workload-aware database monitoring and consolidation
In most enterprises, databases are deployed on dedicated database servers. Often, these servers are underutilized much of the time. For example, in traces from almost 200 producti...
Carlo Curino, Evan P. C. Jones, Samuel Madden, Har...
IJCAI
1997
14 years 11 months ago
Mini-Buckets: A General Scheme for Generating Approximations in Automated Reasoning
The class of algorithms for approximating reasoning tasks presented in this paper is based on approximating the general bucket elimination framework. The algorithms have adjustabl...
Rina Dechter
ICS
2007
Tsinghua U.
15 years 4 months ago
Representation-transparent matrix algorithms with scalable performance
Positive results from new object-oriented tools for scientific programming are reported. Using template classes, abstractions of matrix representations are available that subsume...
Peter Gottschling, David S. Wise, Michael D. Adams