Výsledky vyhledávání - approximate statistics dynamic programming algorithm

LinearFold: linear-time approximate RNA folding by 5'-to-3' dynamic programming and beam search Autor Huang, Liang, Zhang, He, Deng, Dezhong, Zhao, Kai, Liu, Kaibo, Hendrix, David A, Mathews, David H

“… Existing algorithms [based on dynamic programming] suffer from a major limitation: their runtimes scale cubically with the RNA length, and this slowness limits their use in genome-wide applications…”
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An Approximate Dynamic Programming Algorithm for Large-Scale Fleet Management: A Case Application Autor Simao, Hugo P, Day, Jeff, George, Abraham P, Gifford, Ted, Nienow, John, Powell, Warren B

“… The goal of the model was not to obtain a better solution but rather to closely match a number of operational statistics…”
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A Randomized Exchange Algorithm for Computing Optimal Approximate Designs of Experiments Autor Harman, Radoslav, Filová, Lenka, Richtárik, Peter

“…We propose a class of subspace ascent methods for computing optimal approximate designs that covers existing algorithms as well as new and more efficient ones…”
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Energy-Efficient Link Selection and Transmission Scheduling in Mobile Cloud Computing Autor Xiang, Xudong, Chuang, Lin, Chen, Xin

“… To solve the formulated SDP, we then propose a scalable approximate dynamic programming (ADP) algorithm that does not require the statistics of exogenous stochastic information…”
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Approximate dynamic programming methods in Bayesian preference elicitation Autor Fisher, William, Zhang, Qiong, Song, Yongjia

“…Bayesian preference elicitation is a statistical framework which can aid in complex decision making processes such as engineering design by offering…”
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Reinforcement learning-based design of sampling policies under cost constraints in Markov random fields: Application to weed map reconstruction Autor Bonneau, Mathieu, Gaba, Sabrina, Peyrard, Nathalie, Sabbadin, Régis

“…Weeds are responsible for yield losses in arable fields, whereas the role of weeds in agro-ecosystem food webs and in providing ecological services has been…”
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Modeling and Analysis of Baseline Manipulation in Demand Response Programs Autor Wang, Xiaochu, Tang, Wenyuan

“… We investigate the approximation of baseline methods to understand how the method parameters and the consumption statistics would affect the strategic behavior…”
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Metropolis-Hastings via Classification Autor Kaji, Tetsuya, Ročková, Veronika

“…) estimators which can be plugged into the Metropolis-Hastings algorithm. The resulting Markov chains generate, at a steady state, samples from an approximate posterior whose asymptotic properties we characterize…”
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ONLINE CAPACITY PLANNING FOR REHABILITATION TREATMENTS: AN APPROXIMATE DYNAMIC PROGRAMMING APPROACH Autor Bikker, Ingeborg A., Mes, Martijn R.K., Sauré, Antoine, Boucherie, Richard J.

“…We study an online capacity planning problem in which arriving patients require a series of appointments at several departments, within a certain access time…”
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Approximate dynamic programming algorithms for optimal dosage decisions in controlled ovarian hyperstimulation Autor He, Miao, Zhao, Lei, Powell, Warren B.

“… ► Design efficient approximate dynamic programming (ADP) solution algorithms. ► Compare ADP policies with the Markov decision processes (MDP) benchmark…”
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A Bayesian Machine Learning Approach for Optimizing Dynamic Treatment Regimes Autor Murray, Thomas A., Yuan, Ying, Thall, Peter F.

“… These decisions can be formalized as a dynamic treatment regime. This article describes a new approach for optimizing dynamic treatment regimes, which bridges the gap between Bayesian inference and existing approaches, like Q-learning…”
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MIDAS: A mixed integer dynamic approximation scheme Autor Philpott, A. B., Wahid, F., Bonnans, J. F.

“…Mixed integer dynamic approximation scheme (MIDAS) is a new sampling-based algorithm for solving finite-horizon stochastic dynamic programs with monotonic Bellman functions…”
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A multi-criteria approach to approximate solution of multiple-choice knapsack problem Autor Bednarczuk, Ewa M., Miroforidis, Janusz, Pyzel, Przemysław

“…We propose a method for finding approximate solutions to multiple-choice knapsack problems…”
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Dynamic programming approximation algorithms for the capacitated lot-sizing problem Autor Büyüktahtakın, İ. Esra, Liu, Ning

“… The proposed method combines dynamic programming with regression, data fitting, and approximation techniques to estimate the inventory cost function at each stage of the dynamic program…”
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Optimized radial basis function neural network for improving approximate dynamic programming in pricing high dimensional options Autor Hajizadeh, Ehsan, Mahootchi, Masoud

“… In this paper, we develop an optimized radial basis function neural network (RBFNN), which is optimally tuned by the particle swarm optimization algorithm to enhance the efficiency and accuracy of approximate dynamic programming (ADP…”
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Stable iterative adaptive dynamic programming algorithm with approximation errors for discrete-time nonlinear systems Autor Wei, Qinglai, Liu, Derong

“…In this paper, a novel iterative adaptive dynamic programming (ADP) algorithm is developed to solve infinite horizon optimal control problems for discrete-time nonlinear systems…”
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Data mining for state space orthogonalization in adaptive dynamic programming Autor Ariyajunya, Bancha, Chen, Ying, Chen, Victoria C.P., Kim, Seoung Bum

“…•A case study addresses multicollinearity between ozone pollution concentrations. Dynamic programming (DP…”
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On-Policy and Off-Policy Value Iteration Algorithms for Stochastic Zero-Sum Dynamic Games Autor Guo, Liangyuan, Wang, Bing-Chang, Zhang, Ji-Feng

“…This paper considers the value iteration algorithms of stochastic zero-sum linear quadratic games with unkown dynamics…”
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An adaptive dynamic programming-based algorithm for infinite-horizon linear quadratic stochastic optimal control problems Autor Zhang, Heng

“…This paper develops a novel adaptive dynamic programming (ADP)-based model-free policy iteration (PI…”
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Pathwise Optimization for Optimal Stopping Problems Autor Desai, Vijay V., Farias, Vivek F., Moallemi, Ciamac C.

“…We introduce the pathwise optimization (PO) method, a new convex optimization procedure to produce upper and lower bounds on the optimal value (the "price") of…”
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