Results 31 to 40 of about 113,518 (248)
Universal Prediction Band via Semi-Definite Programming [PDF]
Journal of the Royal Statistical Society Series B: Statistical Methodology, 2021 AbstractWe propose a computationally efficient method to construct nonparametric, heteroscedastic prediction bands for uncertainty quantification, with or without any user-specified predictive model. Our approach provides an alternative to the now-standard conformal prediction for uncertainty quantification, with novel theoretical insights and ...
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Mathematics, 2022 This work addresses the robust counterpart of the shortest path problem (RSPP) with a correlated uncertainty set. Because this problem is difficult, a heuristic approach, based on Frank–Wolfe’s algorithm named discrete Frank–Wolfe (DFW), has recently ...
Chifaa Al Dahik +4 more
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A Semi-Definite Programming Approach to Robust Adaptive MPC under State Dependent Uncertainty [PDF]
European Control Conference, 2019 We propose an Adaptive MPC framework for uncertain linear systems to achieve robust satisfaction of state and input constraints. The uncertainty in the system is assumed additive, state dependent, and globally Lipschitz with a known Lipschitz constant ...
Monimoy Bujarbaruah +2 more
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Sensors, 2022 A new positioning algorithm based on RSS measurement is proposed. The algorithm adopts maximum likelihood estimation and semi-definite programming. The received signal strength model is transformed to a non-convex estimator for the positioning of the ...
Weizhong Ding +4 more
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Coupling policy iteration with semi-definite relaxation to compute accurate numerical invariants in static analysis [PDF]
Logical Methods in Computer Science, 2012 We introduce a new domain for finding precise numerical invariants of programs by abstract interpretation. This domain, which consists of level sets of non-linear functions, generalizes the domain of linear "templates" introduced by Manna ...
Assalé Adjé +2 more
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Mathematics, 2022 We consider a variant of the online semi-definite programming problem (OSDP). Specifically, in our problem, the setting of the decision space is a set of positive semi-definite matrices constrained by two norms in parallel: the L∞ norm to the diagonal ...
Yaxiong Liu +3 more
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A semi-definite programming approach to stability analysis of linear partial differential equations [PDF]
IEEE Conference on Decision and Control, 2017 We consider the stability analysis of a large class of linear 1-D PDEs with polynomial data. This class of PDEs contains, as examples, parabolic and hyperbolic PDEs with spatially varying coefficients and systems of in-domain/boundary coupled PDEs.
Aditya Gahlawat, G. Valmorbida
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Linear programming with positive semi definite matrices [PDF]
Proceedings of 1995 34th IEEE Conference on Decision and Control, 1996 We consider the general linear programming problem over the cone of positive semi‐definite matrices. We first provide a simple sufficient condition for existence of optimal solutions and absence of a duality gap without requiring existence of a strictly feasible solution.
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Compressed Sensing Linear Array SAR Autofocusing Imaging via Semi-definite Programming
Leida xuebao, 2018 Linear Array Synthetic Aperture Radar (LASAR) is a novel and promising radar imaging technique. In recent years, Compressed Sensing (CS) sparse recovery has been a research focus for high-resolution three-Dimensional (3-D) LASAR imaging.
Wei Shunjun +3 more
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Parallel Jobs Scheduling with a Specific Due Date: Asemi-definite Relaxation-based Algorithm [PDF]
Journal of Optimization in Industrial Engineering, 2020 This paper considers a different version of the parallel machines scheduling problem in which the parallel jobs simultaneously requirea pre-specifiedjob-dependent number of machines when being processed.This relaxation departs from one of the classic ...
Javad Behnamian
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