Results 11 to 20 of about 4,530,250 (344)
Convex Optimization in R [PDF]
Journal of Statistical Software, 2014 Convex optimization now plays an essential role in many facets of statistics. We briefly survey some recent developments and describe some implementations of these methods in R .
Roger Koenker, Ivan Mizera
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Convex projection and convex multi-objective optimization [PDF]
Journal of Global Optimization, 2021 AbstractIn this paper we consider a problem, called convex projection, of projecting a convex set onto a subspace. We will show that to a convex projection one can assign a particular multi-objective convex optimization problem, such that the solution to that problem also solves the convex projection (and vice versa), which is analogous to the result ...
Gabriela Kováčová, Birgit Rudloff
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Convex Optimization of Bioprocesses
IEEE Transactions on Automatic Control, 2022 We optimize a general model of bioprocesses, which is nonconvex due to the microbial growth in the biochemical reactors. We formulate a convex relaxation and give conditions guaranteeing its exactness in both the transient and steady state cases. When the growth kinetics are modeled by the Monod function under constant biomass or the Contois function ...
Josh A. Taylor +2 more
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Computer Vision, 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
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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
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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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Quantum algorithms and lower bounds for convex optimization [PDF]
Quantum, 2020 While recent work suggests that quantum computers can speed up the solution of semidefinite programs, little is known about the quantum complexity of more general convex optimization.
Shouvanik Chakrabarti +3 more
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An Improved Convergence Analysis for Decentralized Online Stochastic Non-Convex Optimization [PDF]
IEEE Transactions on Signal Processing, 2020 In this paper, we study decentralized online stochastic non-convex optimization over a network of nodes. Integrating a technique called gradient tracking in decentralized stochastic gradient descent, we show that the resulting algorithm, GT-DSGD, enjoys ...
Ran Xin, U. Khan, S. Kar
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An inexact accelerated stochastic ADMM for separable convex optimization [PDF]
Computational optimization and applications, 2020 An inexact accelerated stochastic Alternating Direction Method of Multipliers (AS-ADMM) scheme is developed for solving structured separable convex optimization problems with linear constraints.
Jianchao Bai, W. Hager, Hongchao Zhang
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