11 citations · 46 across the 19 of their papers we have counts for
7 papers · 1 filter
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…
Feasibility of Transfer Learning: A Mathematical Framework
Haoyang Cao, Haotian Gu, Xin Guo
Transfer learning is a popular paradigm for utilizing existing knowledge from previous learning tasks to improve the performance of new ones. It has enjoyed numerous empirical succ…
Feasibility and Transferability of Transfer Learning: A Mathematical Framework
Haoyang Cao, Haotian Gu, Xin Guo +1
Transfer learning is an emerging and popular paradigm for utilizing existing knowledge from previous learning tasks to improve the performance of new ones. Despite its numerous emp…
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]…
SDE approximations of GANs training and its long-run behavior
Haoyang Cao, Xin Guo
This paper analyzes the training process of GANs via stochastic differential equations (SDEs). It first establishes SDE approximations for the training of GANs under stochastic gra…