3 citations · 3 across the 10 of their papers we have counts for
10 papers
Weak-to-Strong Learning in Decision Making
Jingwei Ji, Renyuan Xu
Many operational decisions rely on predictive models that estimate uncertain outcomes conditional on observable contexts. Training such models, however, often faces a fundamental d…
Sobolev Regularized Score Difference Estimation in Diffusion Models
Chenghan Xie, Jose Blanchet, Renyuan Xu
Estimating the difference of two Stein's score functions is a fundamental problem in generative modeling. In particular, score differences arise naturally in transfer learning, whe…
Online Optimization of Difference-of-Convex Compositions with Smooth Mappings
Jingwei Ji, Jong-Shi Pang, Renyuan Xu
We study online optimization for a broad class of structured non-convex non-smooth problems where each loss is a composition of a difference-of-convex function with a smooth mappin…
One-Step Generative Modeling via Wasserstein Gradient Flows
Jiaqi Han, Puheng Li, Qiushan Guo +3
Diffusion models and flow-based methods have shown impressive generative capability, especially for images, but their sampling is expensive because it requires many iterative updat…
Conditional Diffusion Guidance under Hard Constraint: A Stochastic Analysis Approach
Zhengyi Guo, Wenpin Tang, Renyuan Xu
We study conditional generation in diffusion models under hard constraints, where generated samples must satisfy prescribed events with probability one. Such constraints arise natu…
Adaptive Partitioning and Learning for Stochastic Control of Diffusion Processes
Hanqing Jin, Renyuan Xu, Yanzhao Yang
We study reinforcement learning for controlled diffusion processes with unbounded continuous state spaces, bounded continuous actions, and polynomially growing rewards: settings th…
Schrödinger bridge for generative AI: Soft-constrained formulation and convergence analysis
Jin Ma, Ying Tan, Renyuan Xu
Generative AI can be framed as the problem of learning a model that maps simple reference measures into complex data distributions, and it has recently found a strong connection to…
Stochastic Control for Fine-tuning Diffusion Models: Optimality, Regularity, and Convergence
Yinbin Han, Meisam Razaviyayn, Renyuan Xu
Diffusion models have emerged as powerful tools for generative modeling, demonstrating exceptional capability in capturing target data distributions from large datasets. However, f…
Multi-Task Dynamic Pricing in Credit Market with Contextual Information
Adel Javanmard, Jingwei Ji, Renyuan Xu
We study the dynamic pricing problem faced by a broker seeking to learn prices for a large number of credit market securities, such as corporate bonds, government bonds, loans, and…
Neural Network-Based Score Estimation in Diffusion Models: Optimization and Generalization
Yinbin Han, Meisam Razaviyayn, Renyuan Xu
Diffusion models have become a leading paradigm in generative AI, with score estimation via denoising score matching as a central component. While recent theory provides strong sta…