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Efficient Strongly Polynomial Algorithms for Quantile Regression
CoRR, 2023 Linear Regression is a seminal technique in statistics and machine learning, where the objective is to build linear predictive models between a response (i.e., dependent) variable and one or more predictor (i.e., independent) variables. In this paper, we revisit the classical technique of Quantile Regression (QR), which is statistically a more robust ...
Suraj Shetiya +3 more
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Weakly and strongly polynomial algorithms for computing the maximum decrease in uniform arc capacities [PDF]
Yugoslav Journal of Operations Research, 2016 In this paper, a new problem on a directed network is presented. Let D be a feasible network such that all arc capacities are equal to U. Given a t > 0, the network D with arc capacities U - t is called the t-network.
Ghiyasvand Mehdi
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On the energy landscape of symmetric quantum signal processing [PDF]
Quantum, 2022 Symmetric quantum signal processing provides a parameterized representation of a real polynomial, which can be translated into an efficient quantum circuit for performing a wide range of computational tasks on quantum computers. For a given polynomial $f$
Jiasu Wang, Yulong Dong, Lin Lin
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A Strongly Polynomial Algorithm for Controlled Queues [PDF]
Mathematics of Operations Research, 2009 We consider the problem of computing optimal policies of finite-state finite-action Markov decision processes (MDPs). A reduction to a continuum of constrained MDPs (CMDPs) is presented such that the optimal policies for these CMDPs constitute a path in a graph defined over the deterministic policies.
Alexander Zadorojniy +2 more
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An overview on polynomial approximation of NP-hard problems [PDF]
Yugoslav Journal of Operations Research, 2009 The fact that polynomial time algorithm is very unlikely to be devised for an optimal solving of the NP-hard problems strongly motivates both the researchers and the practitioners to try to solve such problems heuristically, by making a trade-off between
Paschos Vangelis Th.
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A strongly polynomial algorithm for linear exchange markets [PDF]
Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing, 2019 We present a strongly polynomial algorithm for computing an equilibrium in Arrow-Debreu exchange markets with linear utilities. Our algorithm is based on a variant of the weakly polynomial Duan–Mehlhorn (DM) algorithm. We use the DM algorithm as a subroutine to identify revealed edges—that is, pairs of agents and goods that must correspond to the best
Jugal Garg, László A. Végh
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Flow Faster: Efficient Decision Algorithms for Probabilistic Simulations [PDF]
Logical Methods in Computer Science, 2008 Strong and weak simulation relations have been proposed for Markov chains, while strong simulation and strong probabilistic simulation relations have been proposed for probabilistic automata.
Lijun Zhang +3 more
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Towards Distributed Lexicographically Fair Resource Allocation with an Indivisible Constraint
Mathematics, 2022 In the cloud computing and big data era, data analysis jobs are usually executed over geo-distributed data centers to make use of data locality. When there are not enough resources to fully meet the demands of all the jobs, allocating resources fairly ...
Chuanyou Li +3 more
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A Strongly Polynomial Algorithm for Generalized Flow Maximization [PDF]
Mathematics of Operations Research, 2014 A strongly polynomial algorithm is given for the generalized flow maximization problem. It uses a new variant of the scaling technique called continuous scaling. The main measure of progress is that within a strongly polynomial number of steps, an arc can be identified that must be tight in every dual optimal solution and thus can be contracted.
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Network Reconfiguration with Orientation-Dependent Transit Times
International Journal of Mathematics and Mathematical Sciences, 2021 Motivated by applications in evacuation planning, we consider a problem of optimizing flow with arc reversals in which the transit time depends on the orientation of the arc.
Hari Nandan Nath +2 more
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