5 papers
The Benefit of Being Bayesian in Online Conformal Prediction
Zhiyu Zhang, Zhou Lu, Heng Yang
Based on the framework of Conformal Prediction (CP), we study the online construction of confidence sets given a black-box machine learning model. By converting the target confiden…
Adapting Prediction Sets to Distribution Shifts Without Labels
Kevin Kasa, Zhiyu Zhang, Heng Yang +1
Recently there has been a surge of interest to deploy confidence set predictions rather than point predictions in machine learning. Unfortunately, the effectiveness of such predict…
Fast TRAC: A Parameter-Free Optimizer for Lifelong Reinforcement Learning
Aneesh Muppidi, Zhiyu Zhang, Heng Yang
A key challenge in lifelong reinforcement learning (RL) is the loss of plasticity, where previous learning progress hinders an agent's adaptation to new tasks. While regularization…
Discounted Adaptive Online Learning: Towards Better Regularization
Zhiyu Zhang, David Bombara, Heng Yang
We study online learning in adversarial nonstationary environments. Since the future can be very different from the past, a critical challenge is to gracefully forget the history w…
Improving Adaptive Online Learning Using Refined Discretization
Zhiyu Zhang, Heng Yang, Ashok Cutkosky +1
We study unconstrained Online Linear Optimization with Lipschitz losses. Motivated by the pursuit of instance optimality, we propose a new algorithm that simultaneously achieves ($…