Results 61 to 70 of about 619,204 (327)
Optimal transport with convex obstacle [PDF]
Journal of Mathematical Analysis and Applications, 2011 AbstractWe consider the Monge transportation problem when the cost is the squared geodesic distance around a convex obstacle. We show that there exists at least one—and in general infinitely many—optimal transport maps.
Cardaliaguet, Pierre, Jimenez, Chloé
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International Journal of Adaptive Control and Signal Processing, EarlyView.The cost as a function of the number of experiments for a non‐symmetric 21×21$$ 21\times 21 $$ system. Four approaches are shown: the proposed stochastic conjugate gradient ILC (SCGILC) method (), deterministic conjugate gradient ILC (), stochastic gradient descent ILC () and deterministic gradient descent ILC ().
Leontine Aarnoudse, Tom Oomen
wiley +1 more source
Efficient Convex Optimization of Reentry Trajectory via the Chebyshev Pseudospectral Method
International Journal of Aerospace Engineering, 2019 A novel sequential convex (SCvx) optimization scheme via the Chebyshev pseudospectral method is proposed for efficiently solving the hypersonic reentry trajectory optimization problem which is highly constrained by heat flux, dynamic pressure, normal ...
Chun-Mei Yu, Dang-Jun Zhao, Ye Yang
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Simultaneous Tensor Completion and Denoising by Noise Inequality Constrained Convex Optimization
IEEE Access, 2019 Convex optimization, rather than a non-convex approach, still play important roles in many computer science applications because of its exactness and efficiency.
Tatsuya Yokota, Hidekata Hontani
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Information-theoretic lower bounds on the oracle complexity of stochastic convex optimization
, 2011 Relative to the large literature on upper bounds on complexity of convex optimization, lesser attention has been paid to the fundamental hardness of these problems.
Agarwal, Alekh +3 more
core +5 more sources
Learning Convex Optimization Models [PDF]
arXiv, 2020 A convex optimization model predicts an output from an input by solving a convex optimization problem. The class of convex optimization models is large, and includes as special cases many well-known models like linear and logistic regression. We propose a heuristic for learning the parameters in a convex optimization model given a dataset of input ...
arxiv
Journal of Mathematical Analysis and Applications, 1986 Given a bounded real function f defined on a closed bounded real interval I, the problem is to find a quasi-convex function f′ so as to minimize the supremum of |f(s)-f′(s)| for all s in I, over the class of all quasi-convex functions f′ on I. This article obtains optimal solutions to the problem and derives their properties. This problem arises in the
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Current and Future Cornea Chip Models for Advancing Ophthalmic Research and Therapeutics
Advanced Biology, EarlyView.This review analyzes cornea chip technology as an innovative solution to corneal blindness and tissue scarcity. The examination encompasses recent developments in biomaterial design and fabrication methods replicating corneal architecture, highlighting applications in drug screening and disease modeling while addressing key challenges in mimicking ...
Minju Kim +3 more
wiley +1 more source
Robust Secure Resource Allocation for RIS-Aided SWIPT Communication Systems
Sensors, 2022 Aiming at the influence of channel uncertainty, user information leakage and harvested energy improvement, this paper proposes a robust resource allocation algorithm for reconfigurable intelligent reflector (RIS) multiple-input single-output systems ...
Bencheng Yu, Zihui Ren, Shoufeng Tang
doaj +1 more source
Identification of Structured LTI MIMO State-Space Models
, 2015 The identification of structured state-space model has been intensively studied for a long time but still has not been adequately addressed. The main challenge is that the involved estimation problem is a non-convex (or bilinear) optimization problem ...
Basri, Ronen +3 more
core +1 more source