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Found 11 papers, 6 papers with code
Query-decision Regression between Shortest Path and Minimum Steiner Tree
Considering a graph with unknown weights, can we find the shortest path for a pair of nodes if we know the minimal Steiner trees associated with some subset of nodes?
VN-Solver: Vision-based Neural Solver for Combinatorial Optimization over Graphs
For optimization problems over graphs, the common practice of neural combinatorial solvers consumes the inputs in the form of adjacency matrices.
Social-Inverse: Inverse Decision-making of Social Contagion Management with Task Migrations
Considering two decision-making tasks $A$ and $B$, each of which wishes to compute an effective \textit{decision} $Y$ for a given \textit{query} $X$, {can we solve task $B$ by using query-decision pairs $(X, Y)$ of $A$ without knowing the latent decision-making model?}
Learning the Propagation of Worms in Wireless Sensor Networks
Wireless sensor networks (WSNs) are composed of spatially distributed sensors and are considered vulnerable to attacks by worms and their variants.
Deep-Steiner: Learning to Solve the Euclidean Steiner Tree Problem
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.
Learnability of Competitive Threshold Models
Modeling the spread of social contagions is central to various applications in social computing.
USCO-Solver: Solving Undetermined Stochastic Combinatorial Optimization Problems
Therefore, we are frequently confronted with combinatorial optimization problems of which the objective function is unknown and thus has to be debunked using empirical evidence.
StratLearner: Learning a Strategy for Misinformation Prevention in Social Networks
Given the examples of attacker-protector pairs, our goal is to learn a strategy to compute protectors against future attackers, without the need of knowing the underlying diffusion model.
SocialGrid: A TCN-enhanced Method for Online Discussion Forecasting
Based on the nature of the grid, we leverage the Temporal Convolution Network to learn the dynamics at the grid level.
Social and Information Networks
NesTPP: Modeling Thread Dynamics in Online Discussion Forums
Online discussion forum creates an asynchronous conversation environment for online users to exchange ideas and share opinions through a unique thread-reply communication mode.
Social and Information Networks
Time-constrained Adaptive Influence Maximization
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 diffusion process.
Social and Information Networks
