Results 31 to 40 of about 26,185 (264)
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
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
GloptiNets: Scalable Non-Convex Optimization with Certificates
Advances in Neural Information Processing Systems 36, 2023 We present a novel approach to non-convex optimization with certificates, which handles smooth functions on the hypercube or on the torus. Unlike traditional methods that rely on algebraic properties, our algorithm exploits the regularity of the target function intrinsic in the decay of its Fourier spectrum. By defining a tractable family of models, we
Beugnot, Gaspard +2 more
openaire +5 more sources
Joint Transceiver Optimization for Multiuser Multi-Antenna Relay Systems With Energy Harvesting
IEEE Access, 2019 In this paper, a multiuser multi-antenna relay system with wireless power transfer is investigated, where the relay node harvests energy from the radio frequency signal sent from the source node and utilizes the harvested energy to forward the ...
Jinlong Wang +4 more
doaj +1 more source
Non-convex scenario optimization
Mathematical ProgrammingAbstract Scenario optimization is an approach to data-driven decision-making that has been introduced some fifteen years ago and has ever since then grown fast. Its most remarkable feature is that it blends the heuristic nature of data-driven methods with a rigorous theory that allows one to gain factual, reliable, insight in the
Simone Garatti, Marco C. Campi
openaire +3 more sources
Online Non-convex Optimization with Long-term Non-convex Constraints
, 2023 A novel Follow-the-Perturbed-Leader type algorithm is proposed and analyzed for solving general long-term constrained optimization problems in an online manner, where the target and constraint functions are oblivious adversarially generated and not necessarily convex. The algorithm is based on Lagrangian reformulation and innovatively integrates random
Pan, Shijie, Xu, Jianyu, Huang, Wenjie
openaire +2 more sources
Applied Sciences, 2020 With the joint optimization of the electricity−gas−heating system (EGHS) attracting more and more attention, a distributed optimized scheduling framework for EGHS based on an improved alternating direction method of multipliers (ADMM ...
Hanxin Zhu +3 more
doaj +1 more source
Sensors, 2013 Deployment is a critical issue affecting the quality of service of camera networks. The deployment aims at adopting the least number of cameras to cover the whole scene, which may have obstacles to occlude the line of sight, with expected observation ...
Guangming Shi +3 more
doaj +1 more source
IEEE Access, 2021 This paper discusses the problem of fault estimation for two-dimensional (2-D) Fornasini-Marchesini (FM) dynamical systems. The objective of this paper is to design a fault estimation filter to reconstruct the characteristics of faults in low-frequency ...
Xiao-Xue Wu, Yunxia Xia, He-Ping Liu
doaj +1 more source
Sample-and-Bound for Non-convex Optimization
Proceedings of the AAAI Conference on Artificial IntelligenceStandard approaches for global optimization of non-convex functions, such as branch-and-bound, maintain partition trees to systematically prune the domain. The tree size grows exponentially in the number of dimensions. We propose new sampling-based methods for non-convex optimization that adapts Monte Carlo Tree Search (MCTS) to improve efficiency ...
Yaoguang Zhai, Zhizhen Qin, Sicun Gao
openaire +4 more sources