4 papers
Diff2SP: Diffusion Models for Correlated Scenario Generation in Stochastic Programming
Haixiang Sun, Andrew Liu
Scenario generation is a critical component in stochastic programming (SP), as it directly influences the quality of decision-making under uncertainty. Existing approaches predomin…
Robust Generalization with Adaptive Optimal Transport Priors for Decision-Focused Learning
Haixiang Sun, Andrew L. Liu
Few-shot learning requires models to generalize under limited supervision while remaining robust to distribution shifts. Existing Sinkhorn Distributionally Robust Optimization (DRO…
Efficient Causal Structure Learning via Modular Subgraph Integration
Haixiang Sun, Pengchao Tian, Zihan Zhou +3
Learning causal structures from observational data remains a fundamental yet computationally intensive task, particularly in high-dimensional settings where existing methods face c…
FedFetch: Faster Federated Learning with Adaptive Downstream Prefetching
Qifan Yan, Andrew Liu, Shiqi He +2
Federated learning (FL) is a machine learning paradigm that facilitates massively distributed model training with end-user data on edge devices directed by a central server. Howeve…