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» Global Optimization for Value Function Approximation
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114
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ICML
2003
IEEE
16 years 3 months ago
Action Elimination and Stopping Conditions for Reinforcement Learning
We consider incorporating action elimination procedures in reinforcement learning algorithms. We suggest a framework that is based on learning an upper and a lower estimates of th...
Eyal Even-Dar, Shie Mannor, Yishay Mansour
128
Voted
SODA
2010
ACM
164views Algorithms» more  SODA 2010»
16 years 5 days ago
Differentially Private Approximation Algorithms
Consider the following problem: given a metric space, some of whose points are "clients," select a set of at most k facility locations to minimize the average distance f...
Anupam Gupta, Katrina Ligett, Frank McSherry, Aaro...
134
Voted
PODS
2008
ACM
159views Database» more  PODS 2008»
16 years 2 months ago
Approximation algorithms for clustering uncertain data
There is an increasing quantity of data with uncertainty arising from applications such as sensor network measurements, record linkage, and as output of mining algorithms. This un...
Graham Cormode, Andrew McGregor
111
Voted
ICDCS
2005
IEEE
15 years 8 months ago
Optimal Component Composition for Scalable Stream Processing
Stream processing has become increasingly important with emergence of stream applications such as audio/video surveillance, stock price tracing, and sensor data analysis. A challe...
Xiaohui Gu, Philip S. Yu, Klara Nahrstedt
142
Voted
MCS
2010
Springer
15 years 1 months ago
Goal-oriented a posteriori error estimates for transport problems
Some aspects of goal-oriented a posteriori error estimation are addressed in the context of steady convection-diffusion equations. The difference between the exact and approxima...
Dmitri Kuzmin, Sergey Korotov