Results 1 to 10 of about 4,225,137 (151)
Quasi-Herglotz functions and convex optimization. [PDF]
R Soc Open Sci, 2020 We introduce the set of quasi-Herglotz functions and demonstrate that it has properties useful in the modelling of non-passive systems. The linear space of quasi-Herglotz functions constitutes a natural extension of the convex cone of Herglotz functions.
Ivanenko Y +5 more
europepmc +2 more sources
Implementable tensor methods in unconstrained convex optimization. [PDF]
Math Program, 2021 Nesterov Y.
europepmc +2 more sources
Motion planning around obstacles with convex optimization [PDF]
Science Robotics, 2022 From quadrotors delivering packages in urban areas to robot arms moving in confined warehouses, motion planning around obstacles is a core challenge in modern robotics.
Tobia Marcucci +3 more
semanticscholar +1 more source
Quasi Semi and Pseudo Semi (p,E)-Convexity in Non-Linear Optimization Programming
Ibn Al-Haitham Journal for Pure and Applied Sciences, 2023 The class of quasi semi -convex functions and pseudo semi -convex functions are presented in this paper by combining the class of -convex functions with the class of quasi semi -convex functions and pseudo semi -convex functions, respectively.
Revan I. Hazim, Saba N. Majeed
doaj +1 more source
Private stochastic convex optimization: optimal rates in linear time [PDF]
Symposium on the Theory of Computing, 2020 We study differentially private (DP) algorithms for stochastic convex optimization: the problem of minimizing the population loss given i.i.d. samples from a distribution over convex loss functions. A recent work of Bassily et al.
V. Feldman, Tomer Koren, Kunal Talwar
semanticscholar +1 more source
Optimization Method for Wide Beam Sonar Transmit Beamforming
Sensors, 2022 Imaging and mapping sonars such as forward-looking sonars (FLS) and side-scan sonars (SSS) are sensors frequently used onboard autonomous underwater vehicles.
Louise Rixon Fuchs +2 more
doaj +1 more source
IEEE Transactions on Automatic Control, 2010 This textbook is based on lectures given by the authors at MIPT (Moscow), HSE (Moscow), FEFU (Vladivostok), V.I. Vernadsky KFU (Simferopol), ASU (Republic of Adygea), and the University of Grenoble-Alpes (Grenoble, France).
Stephen P. Boyd, L. Vandenberghe
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Exact Matrix Completion via Convex Optimization [PDF]
Foundations of Computational Mathematics, 2008 We consider a problem of considerable practical interest: the recovery of a data matrix from a sampling of its entries. Suppose that we observe m entries selected uniformly at random from a matrix M.
E. Candès, B. Recht
semanticscholar +1 more source
Resource Configuration for Throughput Maximization in UAV-WPCN With Intelligent Reflecting Surface
IEEE Access, 2023 UAV-based wireless powered communication network is a promising method of power supply for battery-free IoT devices, but the limited wireless transmission capability of the UAV constrains the coverage area and transmission throughput.
Liang Xue +5 more
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Meta-Learning With Differentiable Convex Optimization [PDF]
Computer Vision and Pattern Recognition, 2019 Many meta-learning approaches for few-shot learning rely on simple base learners such as nearest-neighbor classifiers. However, even in the few-shot regime, discriminatively trained linear predictors can offer better generalization.
Kwonjoon Lee +3 more
semanticscholar +1 more source