5 citations · 5 across the 6 of their papers we have counts for
9 papers
Heavy-Tailed Flow Matching via Random Clocks
Zhouhao Yang, Yezhen Wang, Kenji Kawaguchi +2
Heavy-tailed data arise in many domains where rare events carry disproportionate importance, such as imbalanced image datasets, financial returns, and weather extremes. Standard di…
Diffusion Models for Adaptive Sequential Data Generation
Haoyang Cao, Minshuo Chen, Yinbin Han +1
Generating realistic synthetic sequential data is critical in real-world applications across operations research, finance, healthcare, energy systems, and scientific computing, whe…
Sample Complexity of Transfer Learning: An Optimal Transport Approach
Haoyang Cao, Xin Guo, Wenpin Tang +1
Transfer learning is an essential technique for many machine learning/AI models of complex structures such as large language models and generative AI. The essence of transfer learn…
Scalable Bi-causal Optimal Transport via KL Relaxation and Policy Gradients
Haoyang Cao, Jesse Hoekstra, Renyuan Xu +2
Bi-causal optimal transport (OT) is a natural framework for comparing and coupling stochastic processes under nonanticipative information constraints, with important applications i…
Meta-learning with GANs for anomaly detection, with deployment in high-speed rail inspection system
Haoyang Cao, Xin Guo, Guan Wang
Anomaly detection has been an active research area with a wide range of potential applications. Key challenges for anomaly detection in the AI era with big data include lack of pri…
Identifiability in inverse reinforcement learning
Haoyang Cao, Samuel N. Cohen, Lukasz Szpruch
Inverse reinforcement learning attempts to reconstruct the reward function in a Markov decision problem, using observations of agent actions. As already observed in Russell [1998]…