Search Results - "Approximation Algorithms"

Corrections to "Enhancing Knapsack-Based Financial Portfolio Optimization Using Quantum Approximate Optimization Algorithm" by Huot, Chansreynich, Kea, Kimleang, Kim, Tae-Kyung, Han, Youngsun

“…Presents corrections to the paper, (Corrections to "Enhancing Knapsack-Based Financial Portfolio Optimization Using Quantum Approximate Optimization…”
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Learning Spatial-Temporal Regularized Correlation Filters for Visual Tracking by Li, Feng, Tian, Cheng, Zuo, Wangmeng, Zhang, Lei, Yang, Ming-Hsuan

“…Discriminative Correlation Filters (DCF) are efficient in visual tracking but suffer from unwanted boundary effects. Spatially Regularized DCF (SRDCF) has been…”
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Strong NP-hardness of AC power flows feasibility by Bienstock, Daniel, Verma, Abhinav

“…We prove that testing feasibility for an AC power flow system is a strongly NP-hard problem…”
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Channel Estimation for RIS-Empowered Multi-User MISO Wireless Communications by Wei, Li, Huang, Chongwen, Alexandropoulos, George C., Yuen, Chau, Zhang, Zhaoyang, Debbah, Merouane

“…Reconfigurable Intelligent Surfaces (RISs) have been recently considered as an energy-efficient solution for future wireless networks due to their fast and…”
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Efficient Temporal Simple Path Graph Generation by Tang, Zhiyang, Wu, Yanping, Zai, Xiangjun, Chen, Chen, Wang, Xiaoyang, Zhang, Ying

“…Interactions between two entities often occur at specific timestamps, which can be modeled as a temporal graph. Exploring the relationships between vertices…”
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A Surrogate-Assisted Reference Vector Guided Evolutionary Algorithm for Computationally Expensive Many-Objective Optimization by Chugh, Tinkle, Jin, Yaochu, Miettinen, Kaisa, Hakanen, Jussi, Sindhya, Karthik

“…We propose a surrogate-assisted reference vector guided evolutionary algorithm (EA) for computationally expensive optimization problems with more than three…”
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Weighted Sum-Rate Maximization for Reconfigurable Intelligent Surface Aided Wireless Networks by Guo, Huayan, Liang, Ying-Chang, Chen, Jie, Larsson, Erik G.

“…Reconfigurable intelligent surfaces (RIS) is a promising solution to build a programmable wireless environment via steering the incident signal in fully…”
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AMP-Inspired Deep Networks for Sparse Linear Inverse Problems by Borgerding, Mark, Schniter, Philip, Rangan, Sundeep

“…Deep learning has gained great popularity due to its widespread success on many inference problems. We consider the application of deep learning to the sparse…”
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Time-Varying Convex Optimization: Time-Structured Algorithms and Applications by Simonetto, Andrea, Dall'Anese, Emiliano, Paternain, Santiago, Leus, Geert, Giannakis, Georgios B.

“…Optimization underpins many of the challenges that science and technology face on a daily basis. Recent years have witnessed a major shift from traditional…”
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Markov \alpha-Potential Games by Guo, Xin, Li, Xinyu, Maheshwari, Chinmay, Sastry, Shankar, Wu, Manxi

“…We propose a new framework of Markov <inline-formula><tex-math notation="LaTeX">\alpha</tex-math></inline-formula>-potential games to study Markov games. We…”
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Deep Reinforcement Learning for Autonomous Internet of Things: Model, Applications and Challenges by Lei, Lei, Tan, Yue, Zheng, Kan, Liu, Shiwen, Zhang, Kuan, Shen, Xuemin

“…The Internet of Things (IoT) extends the Internet connectivity into billions of IoT devices around the world, where the IoT devices collect and share…”
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A Simple Local Minimal Intensity Prior and an Improved Algorithm for Blind Image Deblurring by Wen, Fei, Ying, Rendong, Liu, Yipeng, Liu, Peilin, Truong, Trieu-Kien

“…Blind image deblurring is a long standing challenging problem in image processing and low-level vision. Recently, sophisticated priors such as dark channel…”
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Capacity-Achieving Guessing Random Additive Noise Decoding by Duffy, Ken R., Li, Jiange, Medard, Muriel

“…We introduce a new algorithm for realizing maximum likelihood (ML) decoding for arbitrary codebooks in discrete channels with or without memory, in which the…”
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Explainable Machine Learning for Scientific Insights and Discoveries by Roscher, Ribana, Bohn, Bastian, Duarte, Marco F., Garcke, Jochen

“…Machine learning methods have been remarkably successful for a wide range of application areas in the extraction of essential information from data. An…”
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Distributional Soft Actor-Critic: Off-Policy Reinforcement Learning for Addressing Value Estimation Errors by Duan, Jingliang, Guan, Yang, Li, Shengbo Eben, Ren, Yangang, Sun, Qi, Cheng, Bo

“…In reinforcement learning (RL), function approximation errors are known to easily lead to the <inline-formula> <tex-math notation="LaTeX">Q…”
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Efficient and Robust Approximate Nearest Neighbor Search Using Hierarchical Navigable Small World Graphs by Malkov, Yu A., Yashunin, D. A.

“…We present a new approach for the approximate K-nearest neighbor search based on navigable small world graphs with controllable hierarchy (Hierarchical NSW,…”
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Federated Learning Via Inexact ADMM by Zhou, Shenglong, Li, Geoffrey Ye

“…One of the crucial issues in federated learning is how to develop efficient optimization algorithms. Most of the current ones require full device participation…”
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Learning to Optimize: Training Deep Neural Networks for Interference Management by Sun, Haoran, Chen, Xiangyi, Shi, Qingjiang, Hong, Mingyi, Fu, Xiao, Sidiropoulos, Nicholas D.

“…Numerical optimization has played a central role in addressing key signal processing (SP) problems. Highly effective methods have been developed for a large…”
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Matrix-Calibration-Based Cascaded Channel Estimation for Reconfigurable Intelligent Surface Assisted Multiuser MIMO by Liu, Hang, Yuan, Xiaojun, Zhang, Ying-Jun Angela

“…Reconfigurable intelligent surface (RIS) is envisioned to be an essential component of the paradigm for beyond 5G networks as it can potentially provide…”
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Compressive Sensing-Based Adaptive Active User Detection and Channel Estimation: Massive Access Meets Massive MIMO by Ke, Malong, Gao, Zhen, Wu, Yongpeng, Gao, Xiqi, Schober, Robert

“…This paper considers massive access in massive multiple-input multiple-output (MIMO) systems and proposes an adaptive active user detection and channel…”
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