225 citations · 333 across the 27 of their papers we have counts for
7 papers · 1 filter
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…
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…