18 citations · 52 across the 23 of their papers we have counts for
6 papers · 1 filter
Lifting the Veil: Unlocking the Power of Depth in Q-learning
Shao-Bo Lin, Tao Li, Shaojie Tang +2
With the help of massive data and rich computational resources, deep Q-learning has been widely used in operations research and management science and has contributed to great succ…
Adaptive Distributed Kernel Ridge Regression: A Feasible Distributed Learning Scheme for Data Silos
Di Wang, Xiaotong Liu, Shao-Bo Lin +1
Data silos, mainly caused by privacy and interoperability, significantly constrain collaborations among different organizations with similar data for the same purpose. Distributed…
Optimal Approximation and Learning Rates for Deep Convolutional Neural Networks
Shao-Bo Lin
This paper focuses on approximation and learning performance analysis for deep convolutional neural networks with zero-padding and max-pooling. We prove that, to approximate -sm…
Deep Convolutional Neural Networks with Zero-Padding: Feature Extraction and Learning
Zhi Han, Baichen Liu, Shao-Bo Lin +1
This paper studies the performance of deep convolutional neural networks (DCNNs) with zero-padding in feature extraction and learning. After verifying the roles of zero-padding in…
Sketching with Spherical Designs for Noisy Data Fitting on Spheres
Shao-Bo Lin, Di Wang, Ding-Xuan Zhou
This paper proposes a sketching strategy based on spherical designs, which is applied to the classical spherical basis function approach for massive spherical data fitting. We cond…
Kernel-Based Distributed Q-Learning: A Scalable Reinforcement Learning Approach for Dynamic Treatment Regimes
Di Wang, Yao Wang, Shao-Bo Lin
In recent years, large amounts of electronic health records (EHRs) concerning chronic diseases have been collected to facilitate medical diagnosis. Modeling the dynamic properties…