225 citations · 333 across the 27 of their papers we have counts for
27 papers
Advances in Set Function Learning: A Survey of Techniques and Applications
Jiahao Xie, Guangmo Tong
Set function learning has emerged as a crucial area in machine learning, addressing the challenge of modeling functions that take sets as inputs. Unlike traditional machine learnin…
VN-Solver: Vision-based Neural Solver for Combinatorial Optimization over Graphs
Mina Samizadeh, Guangmo Tong
Data-driven approaches have been proven effective in solving combinatorial optimization problems over graphs such as the traveling salesman problems and the vehicle routing problem…
Social-Inverse: Inverse Decision-making of Social Contagion Management with Task Migrations
Guangmo Tong
Considering two decision-making tasks and , each of which wishes to compute an effective \textit{decision} for a given \textit{query} , {can we solve task by usin…
Learning the Propagation of Worms in Wireless Sensor Networks
Yifan Wang, Siqi Wang, Guangmo Tong
Wireless sensor networks (WSNs) are composed of spatially distributed sensors and are considered vulnerable to attacks by worms and their variants. Due to the distinct strategies o…
Deep-Steiner: Learning to Solve the Euclidean Steiner Tree Problem
Siqi Wang, Yifan Wang, Guangmo Tong
The Euclidean Steiner tree problem seeks the min-cost network to connect a collection of target locations, and it underlies many applications of wireless networks. In this paper, w…
Learnability of Competitive Threshold Models
Yifan Wang, Guangmo Tong
Modeling the spread of social contagions is central to various applications in social computing. In this paper, we study the learnability of the competitive threshold model from a…
USCO-Solver: Solving Undetermined Stochastic Combinatorial Optimization Problems
Guangmo Tong
Real-world decision-making systems are often subject to uncertainties that have to be resolved through observational data. Therefore, we are frequently confronted with combinatoria…
StratLearner: Learning a Strategy for Misinformation Prevention in Social Networks
Guangmo Tong
Given a combinatorial optimization problem taking an input, can we learn a strategy to solve it from the examples of input-solution pairs without knowing its objective function? In…
SocialGrid: A TCN-enhanced Method for Online Discussion Forecasting
Chen Ling, Ruiqi Wang, Guangmo Tong
As a means of modern communication tools, online discussion forums have become an increasingly popular platform that allows asynchronous online interactions. People share thoughts…
NesTPP: Modeling Thread Dynamics in Online Discussion Forums
Chen Ling, Guangmo Tong, Mozi Chen
Online discussion forum creates an asynchronous conversation environment for online users to exchange ideas and share opinions through a unique thread-reply communication mode. Acc…
WatchDog: Real-time Vehicle Tracking on Geo-distributed Edge Nodes
Zheng Dong, Yan Lu, Guangmo Tong +3
Vehicle tracking, a core application to smart city video analytics, is becoming more widely deployed than ever before thanks to the increasing number of traffic cameras and recent…
Time-constrained Adaptive Influence Maximization
Guangmo Tong, Ruiqi Wang, Zheng Dong +1
The well-known influence maximization problem aims at maximizing the influence of one information cascade in a social network by selecting appropriate seed users prior to the diffu…
On Multi-Cascade Influence Maximization: Model, Hardness and Algorithmic Framework
Guangmo Tong, Ruiqi Wang, Zheng Dong
This paper studies the multi-cascade influence maximization problem, which explores strategies for launching one information cascade in a social network with multiple existing casc…
Adaptive Influence Maximization under General Feedback Models
Guangmo Tong, Ruiqi Wang
Influence maximization is a prototypical problem enabling applications in various domains, and it has been extensively studied in the past decade. The classic influence maximizatio…
Beyond Uniform Reverse Sampling: A Hybrid Sampling Technique for Misinformation Prevention
Gunagmo Tong, Ding-Zhu Du
Online misinformation has been considered as one of the top global risks as it may cause serious consequences such as economic damages and public panic. The misinformation preventi…
Approximation Algorithm for the Partial Set Multi-Cover Problem
Yishuo Shi, Yingli Ran, Zhao Zhang +3
Partial set cover problem and set multi-cover problem are two generalizations of set cover problem. In this paper, we consider the partial set multi-cover problem which is a combin…
An Approximation Algorithm for Active Friending in Online Social Networks
Guangmo Tong, Ruiqi Wang, Xiang Li +2
Guiding users to actively expanding their online social circles is one of the primary strategies for enhancing user participation and growing online social networks. In this paper,…
On Misinformation Containment in Online Social Networks
Guangmo Tong, Weili Wu, Ding-Zhu Du
The widespread online misinformation could cause public panic and serious economic damages. The misinformation containment problem aims at limiting the spread of misinformation in…
Coupon Advertising in Online Social Systems: Algorithms and Sampling Techniques
Guangmo Tong, Weili Wu, Ding-Zhu Du
Online social systems have become important platforms for viral marketing where the advertising of products is carried out with the communication of users. After adopting the produ…
Distributed Rumor Blocking with Multiple Positive Cascades
Guangmo Amo Tong, Weili Wu, Ding-Zhu Du
Misinformation and rumor can spread rapidly and widely through online social networks and therefore rumor controlling has become a critical issue. It is often assumed that there is…
On Rivest-Vuillemin Conjecture for Fourteen Variables
Guangmo Tong, Weili Wu, Ding-Zhu Du
A boolean function is \textit{weakly symmetric} if it is invariant under a transitive permutation group on its variables. A boolean function is \t…
An Efficient Randomized Algorithm for Rumor Blocking in Online Social Networks
Guangmo Tong, Weili Wu, Ling Guo +4
Social networks allow rapid spread of ideas and innovations while the negative information can also propagate widely. When the cascades with different opinions reaching the same us…
Effector Detection in Social Networks
Guangmo, Tong, Shasha Li +2
In a social network, influence diffusion is the process of spreading innovations from user to user. An activation state identifies who are the active users who have adopted the tar…
Terminal-Set-Enhanced Community Detection in Social Networks
G. Tong, L. Cui, W. Wu +2
Community detection aims to reveal the community structure in a social network, which is one of the fundamental problems. In this paper we investigate the community detection probl…