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Architectures, Protocols and Algorithms of Sensor Networks-Second Edition. [PDF]
Sensors (Basel)Płaczek B.
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Multi-UAV-Borne Surveillance Radar Trajectory Planning Method Based on Imitation Learning. [PDF]
Sensors (Basel)Gao X, Li M, Guan K, Ge J.
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Distributed Optimization for Control
Annual Review of Control, Robotics, and Autonomous Systems, 2018Advances in wired and wireless technology have necessitated the development of theory, models, and tools to cope with the new challenges posed by large-scale control and optimization problems over networks. The classical optimization methodology works under the premise that all problem data are available to a central entity (a computing agent or node).
Angelia Nedic, Ji Liu
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Distributed optimization of codebooks
Signal Processing: Image Communication, 1995Abstract Nowadays, many computer facilities are constituted by a network of general-purpose workstations. The aim of this paper is to show how to combine the available resources of this network in order to deal efficiently with time-consuming image processing algorithms.
Patrick Piscaglia +2 more
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Selfish Distributed Optimization
2012In this talk, we present a selection of important concepts and results in algorithmic game theory in recent years, some of which received the 2012 Godel Prize, along with some applications in distributed settings. A famous solution concept for non-cooperative games is the Nash equilibrium.
Burkhard Monien, Christian Scheideler
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Encoded distributed optimization
2017 IEEE International Symposium on Information Theory (ISIT), 2017Today, many real-world machine learning and data analytics problems are of a scale that requires distributed optimization; unlike in centralized computing, these systems are vulnerable to network and node failures. Recently, coding-theoretic ideas have been applied to mitigate node failures in such distributed computing networks.
Can Karakus +2 more
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On the probability distribution of distributed optimization strategies
2013 IEEE Global Conference on Signal and Information Processing, 2013We study the steady-state probability distribution of diffusion and consensus strategies that employ constant step-sizes to enable continuous adaptation and learning. We show that, in the small step-size regime, the estimation error at each agent approaches a Gaussian distribution.
Jianshu Chen, Ali H. Sayed
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International Joint Conference on Autonomous Agents and Multiagent Systems, 2018
We consider the problem of how a buyer can optimize his utility if he can choose his own valuation distribution in a prior-dependent auction, such as the revenue-optimal auction. The problem is motivated by and equivalent to a type of the market segmentation problem, where a principal tries to select a subset of agents (i.e., a market segment) from the
Weiran Shen, Pingzhong Tang, Yulong Zeng
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We consider the problem of how a buyer can optimize his utility if he can choose his own valuation distribution in a prior-dependent auction, such as the revenue-optimal auction. The problem is motivated by and equivalent to a type of the market segmentation problem, where a principal tries to select a subset of agents (i.e., a market segment) from the
Weiran Shen, Pingzhong Tang, Yulong Zeng
openaire +2 more sources