Results 31 to 40 of about 808,313 (268)
Continuation Methods for Riemannian Optimization
SIAM Journal on Optimization, 2022 Numerical continuation in the context of optimization can be used to mitigate convergence issues due to a poor initial guess. In this work, we extend this idea to Riemannian optimization problems, that is, the minimization of a target function on a Riemannian manifold.
Axel Séguin, Daniel Kressner
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Optimization of traffic light phases at adjacent intersections [PDF]
ITM Web of ConferencesThe article studies the relationships between the time intervals of traffic light phases and intersections. Traffic light objects can be mutually useful in relation to each other if they are correctly adjusted and the existing load is distributed.
Stupin Artem +2 more
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A general decomposition theory for the 1-2-3 Conjecture and locally irregular decompositions [PDF]
Discrete Mathematics & Theoretical Computer Science, 2019 How can one distinguish the adjacent vertices of a graph through an edge-weighting? In the last decades, this question has been attracting increasing attention, which resulted in the active field of distinguishing labellings.
Olivier Baudon +7 more
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Hyper-Heuristic Approach for Tuning Parameter Adaptation in Differential Evolution
AxiomsDifferential evolution (DE) is one of the most promising black-box numerical optimization methods. However, DE algorithms suffer from the problem of control parameter settings.
Vladimir Stanovov +2 more
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Dynamic programming in package Mathematica [PDF]
ITM Web of ConferencesDynamic programming (DP) is a powerful algorithmic technique for solving optimization problems by breaking them down into simpler subproblems. This paper presents an implementation of DP algorithms for two classic optimization problems: the Knapsack ...
Stanimirović Predrag S., Stupin Artem
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Optimal Combination of Tensor Optimization Methods [PDF]
, 2020 We consider the minimization problem of a sum of a number of functions having Lipshitz p-th order derivatives with different Lipschitz constants. In this case, to accelerate optimization, we propose a general framework allowing to obtain near-optimal oracle complexity for each function in the sum separately, meaning, in particular, that the oracle for ...
Dmitry Kamzolov +2 more
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Online Payment Fraud Detection Model Using Machine Learning Techniques
IEEE Access, 2023 In a world where wireless communications are critical for transferring massive quantities of data while protecting against interference, the growing possibility of financial fraud has become a significant concern.
Abdulwahab Ali Almazroi, Nasir Ayub
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Optimal Control in Financial Markets for the Uncertain Volatility Model
MathematicsThis paper generalizes the well-known Black–Scholes model, specifically the uncertain volatility model. To calculate the fair price range of a payment obligation, Hamilton–Jacobi–Bellman equations are derived and transformed into nonlinear heat equations
Grigory Belyavski +3 more
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Methodology for assessing the predicted didactic effects from the use of educational and training tools [PDF]
ITM Web of ConferencesThe assessment of didactic effect is the most important in evaluating the effectiveness of training simulators. Modern methods of training specialists have shown that the most applicable at present is the step-by-step formation of skills and abilities ...
Zhukov Aleksandr +4 more
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Journal of the Royal Statistical Society Series B: Statistical Methodology, 1989 SUMMARY Optimal screening methods from a predictive point of view and a decision theoretical approach are devised and are shown to have a similar form. In the multivariate normal case the optimal screening region is found to be a quadratic function of the screening variables. The results are illustrated by an example.
Turkman, K. F., Amaral Turkman, M. A.
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