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Learning Task-relevant Representations for Generalization v..:

, In: Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining,

Yang, Rui ; Wang, Jie ; Geng, Zijie... - p. 2242-2252 , 2022

Link: https://dl.acm.org/doi/10.1145/3534678.3539391

RT 
T1 <cTitle>Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining</cTitle>: T1 <Title>Learning Task-relevant Representations for Generalization via Characteristic Functions of Reward Sequence Distributions</Title>

UL https://suche.suub.uni-bremen.de/peid=acm-3539391&Exemplar=1&LAN=DE
				
A1 Yang, Rui
A1 Wang, Jie
A1 Geng, Zijie
A1 Ye, Mingxuan
A1 Ji, Shuiwang
A1 Li, Bin
A1 Wu, Feng
PB ACM
YR 2022
K1 characteristic function
K1 generalization
K1 reward sequence
K1 task-relevant representation learning
K1 visual reinforcement learning
K1 Computing methodologies
K1 Machine learning
K1 Learning paradigms
K1 Reinforcement learning
K1 Sequential decision making
K1 Artificial intelligence
K1 Computer vision
K1 Computer vision representations
K1 Image representations
K1 Machine learning approaches
K1 Markov decision processes
SP 2242
OP 2252
LK http://dx.doi.org/https://dl.acm.org/doi/10.1145/3534678.3539391
DO https://dl.acm.org/doi/10.1145/3534678.3539391
SF ELIB - SuUB Bremen

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