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» Detection of Stochastic Processes
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131
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JAIR
2011
144views more  JAIR 2011»
14 years 10 months ago
Non-Deterministic Policies in Markovian Decision Processes
Markovian processes have long been used to model stochastic environments. Reinforcement learning has emerged as a framework to solve sequential planning and decision-making proble...
Mahdi Milani Fard, Joelle Pineau
150
Voted
AAAI
2011
14 years 3 months ago
Sparse Matrix-Variate t Process Blockmodels
We consider the problem of modeling network interactions and identifying latent groups of network nodes. This problem is challenging due to the facts i) that the network nodes are...
Zenglin Xu, Feng Yan, Yuan Qi
161
Voted
KDD
2012
ACM
179views Data Mining» more  KDD 2012»
13 years 6 months ago
Web image prediction using multivariate point processes
In this paper, we investigate a problem of predicting what images are likely to appear on the Web at a future time point, given a query word and a database of historical image str...
Gunhee Kim, Fei-Fei Li, Eric P. Xing
130
Voted
ICML
2006
IEEE
16 years 4 months ago
Probabilistic inference for solving discrete and continuous state Markov Decision Processes
Inference in Markov Decision Processes has recently received interest as a means to infer goals of an observed action, policy recognition, and also as a tool to compute policies. ...
Marc Toussaint, Amos J. Storkey
129
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LICS
2007
IEEE
15 years 10 months ago
Limits of Multi-Discounted Markov Decision Processes
Markov decision processes (MDPs) are controllable discrete event systems with stochastic transitions. The payoff received by the controller can be evaluated in different ways, dep...
Hugo Gimbert, Wieslaw Zielonka