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Security adoption and influence of cyber-insurance markets in heterogeneous networks.

, and . Perform. Evaluation, (2014)

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Security Adoption in Heterogeneous Networks: the Influence of Cyber-Insurance Market., and . Networking (2), volume 7290 of Lecture Notes in Computer Science, page 172-183. Springer, (2012)Connecting the Dots Between MLE and RL for Sequence Generation., , , , and . CoRR, (2018)Investigating the effect of node heterogeneity and network externality on security adoption., and . SIGMETRICS Perform. Evaluation Rev., 39 (3): 52-54 (2011)Molecular Dynamics Study to Investigate the Dimeric Structure of the Full-Length α-Synuclein in Aqueous Solution., , , , , , , , and . J. Chem. Inf. Model., 57 (9): 2281-2293 (September 2017)Local Additivity Based Data Augmentation for Semi-supervised NER., , , , and . EMNLP (1), page 1241-1251. Association for Computational Linguistics, (2020)Texar: A Modularized, Versatile, and Extensible Toolkit for Text Generation., , , , , , , , , and 6 other author(s). CoRR, (2018)TreeMix: Compositional Constituency-based Data Augmentation for Natural Language Understanding., , and . NAACL-HLT, page 5243-5258. Association for Computational Linguistics, (2022)Don't Take It Literally: An Edit-Invariant Sequence Loss for Text Generation., , , , , , , , and . NAACL-HLT, page 2055-2078. Association for Computational Linguistics, (2022)Deep Neural Networks with Massive Learned Knowledge., , , and . EMNLP, page 1670-1679. The Association for Computational Linguistics, (2016)Record-to-Text Generation with Style Imitation., , , , , , and . EMNLP (Findings), volume EMNLP 2020 of Findings of ACL, page 1589-1598. Association for Computational Linguistics, (2020)