An Accelerated Directional Derivative Method for Smooth Stochastic Convex Optimization [PDF]
European Journal of Operational Research, 2018 We consider smooth stochastic convex optimization problems in the context of algorithms which are based on directional derivatives of the objective function.
P. Dvurechensky +2 more
semanticscholar +4 more sources
Corner Detection Using Second-Order Generalized Gaussian Directional Derivative Representations
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2019 Corner detection is a critical component of many image analysis and image understanding tasks, such as object recognition and image matching. Our research indicates that existing corner detection algorithms cannot properly depict the difference between ...
Weichuan Zhang, Chang-Ming Sun
semanticscholar +2 more sources
An introduction to non-smooth convex analysis via multiplicative derivative
Journal of Taibah University for Science, 2019 In this study, *-directional derivative and *-subgradient are defined using the multiplicative derivative, making a new contribution to non-Newtonian calculus for use in non-smooth analysis.
Ali Hakan Tor
doaj +2 more sources
Optimality conditions for set optimization using a directional derivative based on generalized Steiner sets [PDF]
Optimization, 2019 Set-optimization has attracted increasing interest in the last years, as for instance uncertain multiobjective optimization problems lead to such problems with a set-valued objective function.
R. Baier, G. Eichfelder, T. Gerlach
semanticscholar +2 more sources
Students’ understanding of two-variable calculus concepts in mathematics and physics contexts. I. The partial derivative and the directional derivative [PDF]
Physical Review Physics Education ResearchThis study investigated how students reason about the partial derivative and the directional derivative of a multivariable function at a given point, using different graphical representations for the function in the problem statement.
Maria Al Dehaybes +3 more
doaj +2 more sources
Corner Detection and Classification Using Anisotropic Directional Derivative Representations
IEEE Transactions on Image Processing, 2013 This paper proposes a corner detector and classifier using anisotropic directional derivative (ANDD) representations. The ANDD representation at a pixel is a function of the oriented angle and characterizes the local directional grayscale variation ...
Peng-Lang Shui, Weichuan Zhang
semanticscholar +2 more sources
Generalized derivatives and optimization problems for n-dimensional fuzzy-number-valued functions
Open Mathematics, 2020 In this paper, we present the concepts of generalized derivative, directional generalized derivative, subdifferential and conjugate for n-dimensional fuzzy-number-valued functions and discuss the characterizations of generalized derivative and ...
Xie Ting, Gong Zengtai, Li Dapeng
doaj +1 more source
Fast Corner Detection Using Approximate Form of Second-Order Gaussian Directional Derivative
IEEE Access, 2020 High-efficiency image corner detection, one of the most important and critical basic technology in industrial image processing, is to detect point features from an input image in real-time.
Tian Gao +5 more
doaj +1 more source
Review of Shearography for Dual-Directional Measurement
Optics, 2022 Shearography is a coherent optical technique that allows the identification of the first derivative of deformation in the shearing direction. Due to direct measuring strain information, shearography is suited for non-destructive testing and evaluation ...
Bicheng Guo +6 more
doaj +1 more source
Karpatsʹkì Matematičnì Publìkacìï, 2019 We partially reinforce some criteria of $L$-index boundedness in direction for functions analytic in the unit ball. These results describe local behavior of directional derivatives on the circle, estimates of maximum modulus, minimum modulus of analytic ...
A.I. Bandura
doaj +1 more source