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AIPS
2004
13 years 11 months ago
Heuristic Refinements of Approximate Linear Programming for Factored Continuous-State Markov Decision Processes
Approximate linear programming (ALP) offers a promising framework for solving large factored Markov decision processes (MDPs) with both discrete and continuous states. Successful ...
Branislav Kveton, Milos Hauskrecht
AUTOMATICA
2005
116views more  AUTOMATICA 2005»
13 years 10 months ago
Monotonically convergent iterative learning control for linear discrete-time systems
In iterative learning control schemes for linear discrete time systems, conditions to guarantee the monotonic convergence of the tracking9 error norms are derived. By using the Ma...
Kevin L. Moore, Yangquan Chen, Vikas Bahl
ECWEB
2003
Springer
104views ECommerce» more  ECWEB 2003»
14 years 3 months ago
e-Procurement Using Goal Programming
Abstract. e-Procurement is an Internet-based business process for obtaining materials and services and managing their inflow into the organization. In this paper we develop multia...
S. Kameshwaran, Y. Narahari
INFOCOM
2012
IEEE
12 years 18 days ago
Delay optimal multichannel opportunistic access
Abstract—The problem of minimizing queueing delay of opportunistic access of multiple continuous time Markov channels is considered. A new access policy based on myopic sensing a...
Shiyao Chen, Lang Tong, Qing Zhao
IDA
2002
Springer
13 years 10 months ago
Classification with sparse grids using simplicial basis functions
Recently we presented a new approach [20] to the classification problem arising in data mining. It is based on the regularization network approach but in contrast to other methods...
Jochen Garcke, Michael Griebel