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20192021
most citedOnline Influence Maximization under Linear Threshold Model

21 citations · 50 across the 10 of their papers we have counts for

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Showing 2020Show all

5 papers · 1 filter

cs.SI20201 cited

On the Equivalence Between High-Order Network-Influence Frameworks: General-Threshold, Hypergraph-Triggering, and Logic-Triggering Models

Wei Chen, Shang-Hua Teng, Hanrui Zhang

In this paper, we study several high-order network-influence-propagation frameworks and their connection to the classical network diffusion frameworks such as the triggering model…

cs.LG202021 cited

Online Influence Maximization under Linear Threshold Model

Shuai Li, Fang Kong, Kejie Tang +2

Online influence maximization (OIM) is a popular problem in social networks to learn influence propagation model parameters and maximize the influence spread at the same time. Most…

cs.LG2020

Optimization from Structured Samples for Coverage Functions

Wei Chen, Xiaoming Sun, Jialin Zhang +1

We revisit the optimization from samples (OPS) model, which studies the problem of optimizing objective functions directly from the sample data. Previous results showed that we can…

cs.LG20204 cited

(Locally) Differentially Private Combinatorial Semi-Bandits

Xiaoyu Chen, Kai Zheng, Zixin Zhou +3

In this paper, we study Combinatorial Semi-Bandits (CSB) that is an extension of classic Multi-Armed Bandits (MAB) under Differential Privacy (DP) and stronger Local Differential P…

cs.SI20203 cited

Efficient Approximation Algorithms for Adaptive Influence Maximization

Keke Huang, Jing Tang, Kai Han +5

Given a social network and an integer , the influence maximization (IM) problem asks for a seed set of nodes from to maximize the expected number of nodes influe…