6 citations · 6 across the 3 of their papers we have counts for
6 papers
A Sample Reuse Strategy for Dynamic Influence Maximization Problem
Shaofeng Zhang, Shengcai Liu, Ke Tang
Dynamic influence maximization problem (DIMP) aims to maintain a group of influential users within an evolving social network, so that the influence scope can be maximized at any g…
Reliable Robustness Evaluation via Automatically Constructed Attack Ensembles
Shengcai Liu, Fu Peng, Ke Tang
Attack Ensemble (AE), which combines multiple attacks together, provides a reliable way to evaluate adversarial robustness. In practice, AEs are often constructed and tuned by huma…
A New Knowledge Gradient-based Method for Constrained Bayesian Optimization
Wenjie Chen, Shengcai Liu, Ke Tang
Black-box problems are common in real life like structural design, drug experiments, and machine learning. When optimizing black-box systems, decision-makers always consider multip…
Memetic Search for Vehicle Routing with Simultaneous Pickup-Delivery and Time Windows
Shengcai Liu, Ke Tang, Xin Yao
The Vehicle Routing Problem with Simultaneous Pickup-Delivery and Time Windows (VRPSPDTW) has attracted much research interest in the last decade, due to its wide application in mo…
Few-shots Parallel Algorithm Portfolio Construction via Co-evolution
Ke Tang, Shengcai Liu, Peng Yang +1
Generalization, i.e., the ability of solving problem instances that are not available during the system design and development phase, is a critical goal for intelligent systems. A…
Towards Feature-free TSP Solver Selection: A Deep Learning Approach
Kangfei Zhao, Shengcai Liu, Yu Rong +1
The Travelling Salesman Problem (TSP) is a classical NP-hard problem and has broad applications in many disciplines and industries. In a large scale location-based services system,…