activity
20182022
most citedHierarchical fuzzy neural networks with privacy preservation for heterogeneous big data

37 citations · 47 across the 2 of their papers we have counts for

collaborators

8 papers

cs.LG202210 cited

Distributed Semi-supervised Fuzzy Regression with Interpolation Consistency Regularization

Ye Shi, Leijie Zhang, Zehong Cao +2

Recently, distributed semi-supervised learning (DSSL) algorithms have shown their effectiveness in leveraging unlabeled samples over interconnected networks, where agents cannot sh…

cs.LG202237 cited

Hierarchical fuzzy neural networks with privacy preservation for heterogeneous big data

Leijie Zhang, Ye Shi, Yu-Cheng Chang +1

Heterogeneous big data poses many challenges in machine learning. Its enormous scale, high dimensionality, and inherent uncertainty make almost every aspect of machine learning dif…

cs.AI2020

Weak Human Preference Supervision For Deep Reinforcement Learning

Zehong Cao, KaiChiu Wong, Chin-Teng Lin

The current reward learning from human preferences could be used to resolve complex reinforcement learning (RL) tasks without access to a reward function by defining a single fixed…

cs.MM2020

A General Approach for Using Deep Neural Network for Digital Watermarking

Yurui Ming, Weiping Ding, Zehong Cao +1

Technologies of the Internet of Things (IoT) facilitate digital contents such as images being acquired in a massive way. However, consideration from the privacy or legislation pers…

cs.LG2019

Reinforcement Learning from Hierarchical Critics

Zehong Cao, Chin-Teng Lin

In this study, we investigate the use of global information to speed up the learning process and increase the cumulative rewards of reinforcement learning (RL) in competition tasks…

quant-ph2018

Quantum topology identification with deep neural networks and quantum walks

Yurui Ming, Chin-Teng Lin, Stephen D. Bartlett +1

Topologically ordered materials may serve as a platform for new quantum technologies such as fault-tolerant quantum computers. To fulfil this promise, efficient and general methods…