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WSDM
2010
ACM
322views Data Mining» more  WSDM 2010»
15 years 9 months ago
Inferring Search Behaviors Using Partially Observable Markov (POM) Model
This article describes an application of the partially observable Markov (POM) model to the analysis of a large scale commercial web search log. Mathematically, POM is a variant o...
Kuansan Wang, Nikolas Gloy, Xiaolong Li
ATAL
2010
Springer
15 years 23 days ago
Risk-sensitive planning in partially observable environments
Partially Observable Markov Decision Process (POMDP) is a popular framework for planning under uncertainty in partially observable domains. Yet, the POMDP model is riskneutral in ...
Janusz Marecki, Pradeep Varakantham
142
Voted
AAAI
2011
13 years 11 months ago
An Online Spectral Learning Algorithm for Partially Observable Nonlinear Dynamical Systems
Recently, a number of researchers have proposed spectral algorithms for learning models of dynamical systems—for example, Hidden Markov Models (HMMs), Partially Observable Marko...
Byron Boots, Geoffrey J. Gordon
AAAI
2010
15 years 1 months ago
Relational Partially Observable MDPs
Relational Markov Decision Processes (MDP) are a useraction for stochastic planning problems since one can develop abstract solutions for them that are independent of domain size ...
Chenggang Wang, Roni Khardon
114
Voted
WIOPT
2011
IEEE
14 years 3 months ago
Network utility maximization over partially observable Markovian channels
Abstract—This paper considers maximizing throughput utility in a multi-user network with partially observable Markov ON/OFF channels. Instantaneous channel states are never known...
Chih-Ping Li, Michael J. Neely