R
Ravi Varadarajan
Researcher at University of Florida
Publications - 12
Citations - 364
Ravi Varadarajan is an academic researcher from University of Florida. The author has contributed to research in topics: Markov decision process & Constraint (information theory). The author has an hindex of 8, co-authored 12 publications receiving 360 citations.
Papers
More filters
Journal ArticleDOI
Multichain Markov decision processes with a sample path constraint: a decomposition approach
Keith W. Ross,Ravi Varadarajan +1 more
TL;DR: It is established that if there exists a policy that meets the constraint that the long-run average cost be no greater than a given value with probability one, then there exists an e-optimal stationary policy.
Journal ArticleDOI
Markov Decision Processes with Sample Path Constraints: The Communicating Case
Keith W. Ross,Ravi Varadarajan +1 more
TL;DR: Assuming that a policy exists that meets the sample-path constraint, it is established that there exist nearly optimal stationary policies for communicating MDPs and a parametric linear programming algorithm is given to construct nearly optimalstationary policies.
Journal ArticleDOI
An objective function for vertically partitioning relations in distributed databases and its analysis
TL;DR: An objective function for vertical partitioning of relations is derived using the square-error criterion commonly used in data clustering, which is shown to be useful for comparing previously developed algorithms for Vertical partitioning.
Proceedings ArticleDOI
Scheduling data redistribution in distributed databases
TL;DR: The problem of properly scheduling data transfers in order to complete this redistribution process in minimum possible time is investigated and a useful upper bound for optimal solutions is presented.
Proceedings ArticleDOI
A formal approach to the vertical partitioning problem in distributed database design
TL;DR: The n-ary vertical partitioning problem is addressed, and an objective function that generalizes and subsumes earlier work is derived that provides a basis for developing heuristic algorithms for vertical partitions.