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» Quantifying group problem solving with stochastic analysis
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FOCS
2007
IEEE
14 years 2 months ago
Approximation Algorithms for Partial-Information Based Stochastic Control with Markovian Rewards
We consider a variant of the classic multi-armed bandit problem (MAB), which we call FEEDBACK MAB, where the reward obtained by playing each of n independent arms varies according...
Sudipto Guha, Kamesh Munagala
TNN
2010
173views Management» more  TNN 2010»
13 years 2 months ago
Global synchronization for discrete-time stochastic complex networks with randomly occurred nonlinearities and mixed time delays
Abstract--In this paper, the problem of stochastic synchronization analysis is investigated for a new array of coupled discretetime stochastic complex networks with randomly occurr...
Zidong Wang, Yao Wang, Yurong Liu
AI
2000
Springer
13 years 7 months ago
Stochastic dynamic programming with factored representations
Markov decisionprocesses(MDPs) haveproven to be popular models for decision-theoretic planning, but standard dynamic programming algorithms for solving MDPs rely on explicit, stat...
Craig Boutilier, Richard Dearden, Moisés Go...
SIGMOD
2005
ACM
111views Database» more  SIGMOD 2005»
14 years 7 months ago
Efficient Computation of Multiple Group By Queries
Data analysts need to understand the quality of data in the warehouse. This is often done by issuing many Group By queries on the sets of columns of interest. Since the volume of ...
Zhimin Chen, Vivek R. Narasayya
CVPR
2003
IEEE
14 years 9 months ago
Optimal Linear Representations of Images for Object Recognition
Although linear representations are frequently used in image analysis, their performances are seldom optimal in specific applications. This paper proposes a stochastic gradient al...
Xiuwen Liu, Anuj Srivastava, Kyle Gallivan