Search Results for "influence maximization"

LAIM: Linear Algorithm for Influence Maximization Any one using the source code please cite: Wu, Hongchun, et al. "A Linear Time Algorithm for Influence Maximization in Large-Scale Social Networks." International Conference on Neural Information Processing. Springer, Cham, 2017.

This is the source code of our submitted paper titled "CoFIM: A community-based framework for influence maximization on large-scale networks". Please do not use the code for commercial purpose.

This is the code used in the experiments of the following paper: Youze Tang, Yanchen Shi, and Xiaokui Xiao. "Influence Maximization in Near-Linear Time: A Martingale Approach." Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data. ACM, 2015. Please cite the paper if you choose to use the code.

This is the code used in the experiments of the following paper: Youze Tang, Xiaokui Xiao, and Yanchen Shi. "Influence maximization: Near-optimal time complexity meets practical efficiency." Proceedings of the 2014 ACM SIGMOD international conference on Management of data. ACM, 2014. Please cite the paper if you choose to use the code.

...It walks through loading a pretrained network, selecting layers and channels to maximize, computing gradients with respect to the input image, and applying multi-scale “octave” processing to reveal fine and coarse patterns. The code is intentionally compact and exploratory, encouraging users to tweak layers, step sizes, and scales to influence the aesthetic. Although minimal, it illustrates important concepts like feature visualization, activation maximization, and the effect of different receptive fields on the final image.

The is our implementation of our work entitled "Neighborhood Matters: Influence Maximization in Social Networks with Limited Access". We proposed both non-adaptive and adaptive algorithms to maximize the influence spread. Specifically, in the non-adaptive case, a two-stage coordinate descent framework is designed to decide the discount allocation. In the adaptive case, a series of algorithms are devised with performance guarantee.