Search Results - "Randomized algorithms"

Solving the stochastic team orienteering problem: comparing simheuristics with the sample average approximation method by Panadero, Javier, Juan, Angel A., Ghorbani, Elnaz, Faulin, Javier, Pagès‐Bernaus, Adela

“…The team orienteering problem (TOP) is an NP‐hard optimization problem with an increasing number of potential applications in smart cities, humanitarian…”
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A Practical Randomized CP Tensor Decomposition by Battaglino, Casey, Ballard, Grey, Kolda, Tamara G.

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Randomized algorithms for the approximations of Tucker and the tensor train decompositions by Che, Maolin, Wei, Yimin

“…Randomized algorithms provide a powerful tool for scientific computing. Compared with standard deterministic algorithms, randomized algorithms are often faster…”
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Constraint-Tightening and Stability in Stochastic Model Predictive Control by Lorenzen, Matthias, Dabbene, Fabrizio, Tempo, Roberto, Allgower, Frank

“…Constraint tightening to non-conservatively guarantee recursive feasibility and stability in Stochastic Model Predictive Control is addressed. Stability and…”
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Convergence in total variation for the kinetic Langevin algorithm by Lehec, Joseph

“…We prove non-asymptotic total variation estimates for the kinetic Langevin algorithm in high dimension when the target measure satisfies a Poincaré inequality…”
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On adaptive Linear–Quadratic regulators by Shirani Faradonbeh, Mohamad Kazem, Tewari, Ambuj, Michailidis, George

“…Performance of adaptive control policies is assessed through the regret with respect to the optimal regulator, which reflects the increase in the operating…”
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Robust stochastic configuration networks with kernel density estimation for uncertain data regression by Wang, Dianhui, Li, Ming

“…Neural networks have been widely used as predictive models to fit data distribution, and they could be implemented through learning a collection of samples. In…”
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Coordinate descent algorithms by Wright, Stephen J.

“…Coordinate descent algorithms solve optimization problems by successively performing approximate minimization along coordinate directions or coordinate…”
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Agile optimization of a two‐echelon vehicle routing problem with pickup and delivery by do C. Martins, Leandro, Hirsch, Patrick, Juan, Angel A.

“…In this paper, we consider a vehicle routing problem in which a fleet of homogeneous vehicles, initially located at a depot, has to satisfy customers' demands…”
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Fault Detection for Non-Gaussian Processes Using Generalized Canonical Correlation Analysis and Randomized Algorithms by Zhiwen Chen, Ding, Steven X., Tao Peng, Chunhua Yang, Weihua Gui

“…In this paper, we first study a generalized canonical correlation analysis (CCA)-based fault detection (FD) method aiming at maximizing the fault detectability…”
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Stochastic Configuration Networks: Fundamentals and Algorithms by Wang, Dianhui, Li, Ming

“…This paper contributes to the development of randomized methods for neural networks. The proposed learner model is generated incrementally by stochastic…”
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Robust stochastic configuration networks with maximum correntropy criterion for uncertain data regression by Li, Ming, Huang, Changqin, Wang, Dianhui

“…This paper develops a robust stochastic configuration network (RSCN) framework to cope with data modelling problems when the given samples contain noises or…”
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Convergence Properties of the Randomized Extended Gauss--Seidel and Kaczmarz Methods by Ma, Anna, Needell, Deanna, Ramdas, Aaditya

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Insights into randomized algorithms for neural networks: Practical issues and common pitfalls by Li, Ming, Wang, Dianhui

“…Random Vector Functional-link (RVFL) networks, a class of learner models, can be regarded as feed-forward neural networks built with a specific randomized…”
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The Algorithmic Leviathan: Arbitrariness, Fairness, and Opportunity in Algorithmic Decision-Making Systems by Creel, Kathleen, Hellman, Deborah

“…This article examines the complaint that arbitrary algorithmic decisions wrong those whom they affect. It makes three contributions. First, it provides an…”
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A randomized approach to sensor placement with observability assurance by Bopardikar, Shaunak D.

“…Given a linear dynamical system, we provide a probabilistic treatment to the classic problem of placing sensors in a set of candidate locations such that the…”
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The loss of serving in the dark by Azar, Yossi, Cohen, Ilan Reuven, Gamzu, Iftah

“…We study the following balls and bins stochastic process: There is a buffer with B bins, and there is a stream of balls X=〈X1,X2,…,XT〉 such that Xi is the…”
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Asymptotic theory of rerandomization in treatment-control experiments by Li, Xinran, Ding, Peng, Rubin, Donald B

“…Although complete randomization ensures covariate balance on average, the chance of observing significant differences between treatment and control covariate…”
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Application of randomized algorithms to assessment and design of observer-based fault detection systems by Ding, Steven X., Li, Linlin, Krüger, Minjia

“…This work is an attempt to establish a probabilistic framework for the assessment and design of observer-based fault detection systems. The fundament of our…”
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Stochastic configuration networks with robust supervised least squares regression by Chu, Fei, Sun, Zihang, Wang, Yu, Zhang, Yong

“…Stochastic Configuration Networks (SCNs) are widely used in regression modeling to fit data distributions due to their fast convergence and powerful learning…”
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