Results 41 to 50 of about 1,516 (207)
Team Composition in PES2018 Using Submodular Function Optimization
IEEE Access, 2019 With the development of computer game technologies, gameplay becomes very realistic in many sports games, therefore providing appealing play experience to game players.
Yifeng Zeng +3 more
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Toward Optimal Placement of Spatial Sensors to Detect Poisson-Distributed Targets
IEEE Access, 2023 This paper addresses the challenges of optimally placing a finite number of sensors to detect Poisson-distributed targets in a bounded domain. We seek to rigorously account for uncertainty in the target arrival model throughout the problem.
Mingyu Kim +5 more
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Submodular Optimization under Noise
CoRR, 2016 We consider the problem of maximizing a monotone submodular function under noise. There has been a great deal of work on optimization of submodular functions under various constraints, resulting in algorithms that provide desirable approximation guarantees.
Avinatan Hassidim, Yaron Singer
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Minimax Optimization: The Case of Convex-Submodular
CoRR, 2021 Minimax optimization has been central in addressing various applications in machine learning, game theory, and control theory. Prior literature has thus far mainly focused on studying such problems in the continuous domain, e.g., convex-concave minimax optimization is now understood to a significant extent.
Arman Adibi +2 more
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Greedy Sensor Selection for Weighted Linear Least Squares Estimation Under Correlated Noise
IEEE Access, 2022 Optimization of sensor selection has been studied to monitor complex and large-scale systems with data-driven linear reduced-order modeling. An algorithm for greedy sensor selection is presented under the assumption of correlated noise in the sensor ...
Keigo Yamada +3 more
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Learning and Optimization with Submodular Functions
CoRR, 2015 Tech Report - USC Computer Science CS-599, Convex and Combinatorial ...
Bharath Sankaran +4 more
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Optimal approximation for submodular and supermodular optimization with bounded curvature [PDF]
Proceedings of the Twenty-Sixth Annual ACM-SIAM Symposium on Discrete Algorithms, 2014 We design new approximation algorithms for the problems of optimizing submodular and supermodular functions subject to a single matroid constraint. Specifically, we consider the case in which we wish to maximize a monotone increasing submodular function or minimize a monotone decreasing supermodular function with a bounded total curvature c ...
Sviridenko, M, Vondrák, J, Ward, J
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Submodular Norms with Applications To Online Facility Location and Stochastic Probing [PDF]
, 2023 Optimization problems often involve vector norms, which has led to extensive research on developing algorithms that can handle objectives beyond _p norms.
Russo, Matteo +5 more
core +1 more source
Research on caching strategy based on transmission delay in Cell-Free massive MIMO systems
Tongxin xuebao, 2021 To meet the ultra-low latency and ultra-high reliability requirements of users in the future mobile Internet， the wireless caching technology was combined with Cell-Free massive MIMO systems.The caching model was designed based on AP cooperative caching ...
Rui WANG, Min SHEN, Yun HE, Xiangyan LIU
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Entropy, 2018 The ability to integrate information in the brain is considered to be an essential property for cognition and consciousness. Integrated Information Theory (IIT) hypothesizes that the amount of integrated information ( Φ ) in the brain is related to ...
Jun Kitazono +2 more
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