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InfoMSD: an information-maximization self-distillation framework for parameter-efficient fine-tuning on artwork images. [PDF]
Front Artif IntellGuan F, Hong H, Wang Y.
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Computational and modeling approaches for US threshold genetic evaluations of calving ease. [PDF]
JDS CommunTabet JM +3 more
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Spatial Individual-Level Models for Transmission Dynamics of Seasonal Infectious Diseases. [PDF]
Stat MedAbed A, Torabi M, Mashreghi Z.
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Dynamic weight clustered federated learning for IoT DDoS attack detection. [PDF]
Sci RepBeshah YK, Abebe SL, Melaku HM.
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A modeling framework for detecting and leveraging node-level information in Bayesian network inference. [PDF]
BiostatisticsXi X, Ruffieux H.
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ACM Transactions on Knowledge Discovery from Data, 2020
Influence maximization problem attempts to find a small subset of nodes in a social network that makes the expected influence maximized, which has been researched intensively before. Most of the existing literature focus only on maximizing total influence, but it ignores whether the influential distribution is balanced through the network.
Jianxiong Guo, Weili Wu
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Influence maximization problem attempts to find a small subset of nodes in a social network that makes the expected influence maximized, which has been researched intensively before. Most of the existing literature focus only on maximizing total influence, but it ignores whether the influential distribution is balanced through the network.
Jianxiong Guo, Weili Wu
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Continuous Influence Maximization
ACM Transactions on Knowledge Discovery from Data, 2020Imagine we are introducing a new product through a social network, where we know for each user in the network the function of purchase probability with respect to discount. Then, what discounts should we offer to those social network users so that, under a predefined budget, the adoption of the product is maximized in expectation?
Yu Yang +3 more
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Adaptive Influence Maximization
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019Information diffusion and social influence are more and more present in today's Web ecosystem. Having algorithms that optimize the presence and message diffusion on social media is indeed crucial to all actors (media companies, political parties, corporations, etc.) who advertise on the Web.
Bogdan Cautis +2 more
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Large-scale influence maximization with the influence maximization benchmarker suite
Proceedings of the 4th ACM SIGMOD Joint International Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA), 2021Maximizing the influence of a fixed size seed set in a graph was investigated intensively in the past decade. Two very relevant questions are 1) how to solve the influence maximization problem on very large graphs within short time and 2) how to compare possible findings with the current state-of-the-art in a fair manner.
Heiko Geppert +2 more
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2017
This chapter describes the prerequisites—independence and expertise—that intermediaries must possess to perform their crucial functions, exert power over producers and consumers, and influence the market. Independence has structural, economic, and cognitive dimensions.
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This chapter describes the prerequisites—independence and expertise—that intermediaries must possess to perform their crucial functions, exert power over producers and consumers, and influence the market. Independence has structural, economic, and cognitive dimensions.
openaire +2 more sources