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Found 5 papers, 1 papers with code
Learning-Guided Rolling Horizon Optimization for Long-Horizon Flexible Job-Shop Scheduling
Long-horizon combinatorial optimization problems (COPs), such as the Flexible Job-Shop Scheduling Problem (FJSP), often involve complex, interdependent decisions over extended time frames, posing significant challenges for existing solvers.
TLMCM Network for Medical Image Hierarchical Multi-Label Classification
Medical Image Hierarchical Multi-Label Classification (MI-HMC) is of paramount importance in modern healthcare, presenting two significant challenges: data imbalance and \textit{hierarchy constraint}.
SIDGAN: High-Resolution Dubbed Video Generation via Shift-Invariant Learning
Dubbed video generation aims to accurately synchronize mouth movements of a given facial video with driving audio while preserving identity and scene-specific visual dynamics, such as head pose and lighting.
Generalization in Deep RL for TSP Problems via Equivariance and Local Search
Since training on large instances is impractical, we design a novel deep RL approach with a focus on generalizability.
Improving Generalization of Deep Reinforcement Learning-based TSP Solvers
In this work, we propose a novel approach named MAGIC that includes a deep learning architecture and a DRL training method.
