Randomized Experiments
Associative Learning
Random Sampling Method
Reinforcement Schedules
Generalization, Discrimination, and Extinction
Aggregates Classification
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Songsong Tian1, Lusi Li2, Weijun Li3
1Institute of Semiconductors, Chinese Academy of Sciences, Beijing, 100083, China; School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing, 100049, China; Beijing Key Laboratory of Semiconductor Neural Network Intelligent Sensing and Computing Technology, Beijing, 100083, China.
简单的班级增量学习 (FSCIL) 用有限的数据和时间解决了深度学习的限制. 本调查综合了FSCIL理论和应用研究,提供了新的分类和未来方向.
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