6 papers
PA-RNet: Perturbation-Aware Residual Network for Robust Multimodal Time Series Forecasting
Enqiang Zhu, Zhenbin Deng, Shengzhi Wang +2
In real-world applications, multimodal time-series forecasting faces a key challenge: textual information is often useful but unreliable. Auxiliary texts may contain irrelevant, am…
Exact Optimization for Minimum Dominating Sets
Enqiang Zhu, Qiqi Bao, Yu Zhang +2
The Minimum Dominating Set (MDS) problem is a well-established combinatorial optimization problem with numerous real-world applications. Its NP-hard nature makes it increasingly di…
DP-GPT4MTS: Dual-Prompt Large Language Model for Textual-Numerical Time Series Forecasting
Chanjuan Liu, Shengzhi Wang, Enqiang Zhu
Time series forecasting is crucial in strategic planning and decision-making across various industries. Traditional forecasting models mainly concentrate on numerical time series d…
Dynamic Location Search for Identifying Maximum Weighted Independent Sets in Complex Networks
Enqiang Zhu, Chenkai Hao, Chanjuan Liu +1
While Artificial intelligence (AI), including Generative AI, are effective at generating high-quality traffic data and optimization solutions in intelligent transportation systems…
GRALS: GCN-Guided Redundancy-Aware Local Search for Minimum Vertex Cover
Enqiang Zhu, Qiqi Bao, Yu Zhang +1
The minimum vertex cover (MVC) problem seeks to identify the smallest set of vertices that cover all edges in an undirected graph. As a fundamental NP-hard combinatorial optimizati…
Guiding Multi-agent Multi-task Reinforcement Learning by a Hierarchical Framework with Logical Reward Shaping
Chanjuan Liu, Jinmiao Cong, Bingcai Chen +2
Multi-agent hierarchical reinforcement learning (MAHRL) has been studied as an effective means to solve intelligent decision problems in complex and large-scale environments. Howev…