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(Private) Kernelized Bandits with Distributed Biased Feedba..:

, In: Abstract Proceedings of the 2023 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems,

Li, Fengjiao ; Zhou, Xingyu ; Ji, Bo - p. 61-62 , 2023

Link: https://dl.acm.org/doi/10.1145/3578338.3593565

RT 
T1 <cTitle>Abstract Proceedings of the 2023 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems</cTitle>: T1 <Title>(Private) Kernelized Bandits with Distributed Biased Feedback</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-3593565&Exemplar=1&LAN=DE
				
A1 Li, Fengjiao
A1 Zhou, Xingyu
A1 Ji, Bo
PB ACM
YR 2023
K1 bias
K1 communication cost
K1 computation complexity
K1 distributed feedback
K1 kernelized bandits
K1 privacy
K1 regret
K1 Theory of computation
K1 Design and analysis of algorithms
K1 Online algorithms
K1 Online learning algorithms
K1 Computing methodologies
K1 Machine learning
K1 Learning settings
K1 Online learning settings
K1 Computational complexity and cryptography
K1 Complexity theory and logic
K1 Security and privacy
K1 Human and societal aspects of security and privacy
K1 Privacy protections
K1 Communication complexity
SP 61
OP 62
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3578338.3593565
DO https://dl.acm.org/doi/10.1145/3578338.3593565
SF ELIB - SuUB Bremen

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