Our model-independent analysis shows that our regret bound has a better (as com- pared to previous work) dependence on the size of the network. Experimental ...

Mar 1, 2017 · Our model-independent analysis shows that our regret bound has a better (as compared to previous work) dependence on the size of the network.

Diffusion occurs according to an underlying diffusion model. •. • Update parameter estimates. • submodular optimization subroutine probability estimates.

For this, we propose a pairwise-influence semi-bandit feed- back model and develop a LinUCB-based ban- dit algorithm. Our model-independent analysis shows that ...

▷ Aim: Find a subset of users ('seed set') who will influence maximum people to become aware of a product: ▷ Challenge 1: IM is not robust to the choice of the ...

We consider influence maximization (IM) in social networks, which is the problem of maximizing the number of users that become aware of a product by ...

We study the online influence maximization problem in social networks under the independent cascade model.

We study the online influence maximization problem in social networks under the independent cascade model. Specifically, we aim to learn the set of "best ...

This paper proposes a multiple-trial approach to solve IM in the absence of complete information on influence probability, and develops an incremental ...

So we focus on how to use the standard offline influ- ence maximization oracle which finds the best seed set given the edge parameters as input. In this paper, ...