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Incremental event detection via an improved knowledge distillation based model.

, , , , and . Neurocomputing, (September 2023)

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Modeling Rationality: Toward Better Performance Against Unknown Agents in Sequential Games., , , , and . IEEE Trans. Cybern., 54 (5): 2966-2977 (May 2024)LibFewShot: A Comprehensive Library for Few-shot Learning., , , , , , , , , and 1 other author(s). CoRR, (2021)Can we improve meta-learning model in few-shot learning by aligning data distributions?, and . Knowl. Based Syst., (October 2023)LibFewShot: A Comprehensive Library for Few-Shot Learning., , , , , , , , , and 1 other author(s). IEEE Trans. Pattern Anal. Mach. Intell., 45 (12): 14938-14955 (December 2023)Differentiable Meta-learning Model for Few-shot Semantic Segmentation., , , , , and . CoRR, (2019)Incremental event detection via an improved knowledge distillation based model., , , , and . Neurocomputing, (September 2023)Improving the Generalization of Meta-learning on Unseen Domains via Adversarial Shift., and . CoRR, (2021)Differentiable Meta-Learning Model for Few-Shot Semantic Segmentation., , , , , and . AAAI, page 12087-12094. AAAI Press, (2020)DDMA: Discrepancy-Driven Multi-agent Reinforcement Learning., , , , and . PRICAI (3), volume 13631 of Lecture Notes in Computer Science, page 91-105. Springer, (2022)Consistent MetaReg: Alleviating Intra-task Discrepancy for Better Meta-knowledge., , , , and . IJCAI, page 2718-2724. ijcai.org, (2020)Scheduled for July 2020, Yokohama, Japan, postponed due to the Corona pandemic..