Constrained Policy Optimization with Explicit Behavior Density for Offline Reinforcement Learning

1 code implementation • NeurIPS 2023 • Jing Zhang, Chi Zhang, Wenjia Wang, Bing-Yi Jing

Due to the inability to interact with the environment, offline reinforcement learning (RL) methods face the challenge of estimating the Out-of-Distribution (OOD) points.

reinforcement-learning Reinforcement Learning (RL)

Community Detection on Mixture Multi-layer Networks via Regularized Tensor Decomposition

no code implementations • 10 Feb 2020 • Bing-Yi Jing, Ting Li, Zhongyuan Lyu, Dong Xia

We show that the TWIST procedure can accurately detect the communities with small misclassification error as the number of nodes and/or the number of layers increases.

Community Detection Stochastic Block Model +1

Adaptive Scaling

no code implementations • 2 Sep 2017 • Ting Li, Bing-Yi Jing, Ningchen Ying, Xianshi Yu

Simulations are conducted to illustrate the advantages of our new scaling method.

regression

Regularized maximum correntropy machine

no code implementations • 18 Jan 2015 • Jim Jing-Yan Wang, Yunji Wang, Bing-Yi Jing, Xin Gao

To solve this problem, we propose to learn the class label predictors by maximizing the correntropy between the predicted labels and the true labels of the training samples, under the regularized Maximum Correntropy Criteria (MCC) framework.