Publications (27)
Bayesian Distributionally Robust Optimization
Alexander Shapiro, Enlu Zhou, Yifan Lin
We introduce a new framework, Bayesian Distributionally Robust Optimization (Bayesian-DRO), for data-driven stochastic optimization where the underlying distribution is unknown. Ba…
Bayesian Risk Markov Decision Processes
Yifan Lin, Yuxuan Ren, Enlu Zhou
We consider finite-horizon Markov Decision Processes where parameters, such as transition probabilities, are unknown and estimated from data. The popular distributionally robust ap…
Multimodal Contrastive Pretraining of CBCT and IOS for Enhanced Tooth Segmentation
Moo Hyun Son, Juyoung Bae, Zelin Qiu +4
Digital dentistry represents a transformative shift in modern dental practice. The foundational step in this transformation is the accurate digital representation of the patient's…
A Privacy-Preserving Framework for Advertising Personalization Incorporating Federated Learning and Differential Privacy
Xiang Li, Yifan Lin, Yuanzhe Zhang
To mitigate privacy leakage and performance issues in personalized advertising, this paper proposes a framework that integrates federated learning and differential privacy. The sys…
Approximate Bilevel Difference Convex Programming for Bayesian Risk Markov Decision Processes
Yifan Lin, Enlu Zhou
We consider infinite-horizon Markov Decision Processes where parameters, such as transition probabilities, are unknown and estimated from data. The popular distributionally robust…
Bayesian Stochastic Gradient Descent for Stochastic Optimization with Streaming Input Data
Tianyi Liu, Yifan Lin, Enlu Zhou
We consider stochastic optimization under distributional uncertainty, where the unknown distributional parameter is estimated from streaming data that arrive sequentially over time…