Results 21 to 30 of about 24,619 (260)
Applied Sciences, 2016 Convex 1-D first-order total variation (TV) denoising is an effective method for eliminating signal noise, which can be defined as convex optimization consisting of a quadratic data fidelity term and a non-convex regularization term.
Cancan Yi, Yong Lv, Zhang Dang, Han Xiao
doaj +1 more source
Optimality and Stability in Non-Convex Smooth Games
J. Mach. Learn. Res., 2020 Convergence to a saddle point for convex-concave functions has been studied for decades, while recent years has seen a surge of interest in non-convex (zero-sum) smooth games, motivated by their recent wide applications. It remains an intriguing research challenge how local optimal points are defined and which algorithm can converge to such points.
Guojun Zhang +2 more
openaire +4 more sources
Communication and Computation Cooperation in Wireless Network for Mobile Edge Computing
IEEE Access, 2019 The advantages of mobile edge computing (MEC) in lower energy consumption, improved bandwidth and reduced delay have attracted extensive studies. We consider a multiple smart wearable devices (SWDs) single smart mobile device (SMD) MEC system where the ...
Yang Li +4 more
doaj +1 more source
Green resource allocation for mobile edge computing
Digital Communications and Networks, 2023 We investigate the green resource allocation to minimize the energy consumption of the users in mobile edge computing systems, where task offloading decisions, transmit power, and computation resource allocation are jointly optimized.
Anqi Meng +4 more
doaj +1 more source
Robust Optimization for Non-Convex Objectives
CoRR, 2017 We consider robust optimization problems, where the goal is to optimize in the worst case over a class of objective functions. We develop a reduction from robust improper optimization to Bayesian optimization: given an oracle that returns $α$-approximate solutions for distributions over objectives, we compute a distribution over solutions that is $α ...
Robert S. Chen +3 more
openaire +3 more sources
Bayesian Optimization Based Efficient Layer Sharing for Incremental Learning
Applied Sciences, 2021 Incremental learning is a methodology that continuously uses the sequential input data to extend the existing network’s knowledge. The layer sharing algorithm is one of the representative methods which leverages general knowledge by sharing some initial ...
Bomi Kim, Taehyeon Kim, Yoonsik Choe
doaj +1 more source
RBCC Mid-section Combined Trajectory Optimization Method Based on Particle Swarm-Pseudospectral Convex Optimization [PDF]
Hangkong bingqiIn order to solve the problem of combined trajectory optimization of RBCC mid-section, a nested optimization method based on particle swarm-pseudospectral convex optimization is proposed.
Yang Yuxuan, Fei Wanghua, Liu Haili, Wang Peichen, Yan Xunliang
doaj +1 more source
Beam Allocation and Power Optimization for Energy-Efficiency in Multiuser mmWave Massive MIMO System
Sensors, 2021 This paper studies beam allocation and power optimization scheme to decrease the hardware cost and downlink power consumption of a multiuser millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) system.
Saidiwaerdi Maimaiti +3 more
doaj +1 more source
On-line Non-Convex Constrained Optimization
CoRR, 2019 Time-varying non-convex continuous-valued non-linear constrained optimization is a fundamental problem. We study conditions wherein a momentum-like regularising term allow for the tracking of local optima by considering an ordinary differential equation (ODE). We then derive an efficient algorithm based on a predictor-corrector method, to track the ODE
Olivier Massicot, Jakub Marecek
openaire +2 more sources
Sparse recovery by non-convex optimization – instance optimality
Applied and Computational Harmonic Analysis, 2010 In this note, we address the theoretical properties of $Δ_p$, a class of compressed sensing decoders that rely on $\ell^p$ minimization with ...
Rayan Saab, Özgür Yilmaz
openaire +2 more sources