354 citations · 2.1k across the 86 of their papers we have counts for
10 papers · 1 filter
Detecting Cyberattacks in Industrial Control Systems Using Online Learning Algorithms
Guangxia Lia, Yulong Shena, Peilin Zhaob +4
Industrial control systems are critical to the operation of industrial facilities, especially for critical infrastructures, such as refineries, power grids, and transportation syst…
Mastering Complex Control in MOBA Games with Deep Reinforcement Learning
Deheng Ye, Zhao Liu, Mingfei Sun +15
We study the reinforcement learning problem of complex action control in the Multi-player Online Battle Arena (MOBA) 1v1 games. This problem involves far more complicated state and…
Data Analytics for Fog Computing by Distributed Online Learning with Asynchronous Update
Guangxia Li, Peilin Zhao, Xiao Lu +2
Fog computing extends the cloud computing paradigm by allocating substantial portions of computations and services towards the edge of a network, and is, therefore, particularly su…
Online Adaptive Asymmetric Active Learning with Limited Budgets
Yifan Zhang, Peilin Zhao, Shuaicheng Niu +4
Online Active Learning (OAL) aims to manage unlabeled datastream by selectively querying the label of data. OAL is applicable to many real-world problems, such as anomaly detection…
Collaborative Unsupervised Domain Adaptation for Medical Image Diagnosis
Yifan Zhang, Ying Wei, Peilin Zhao +4
Deep learning based medical image diagnosis has shown great potential in clinical medicine. However, it often suffers two major difficulties in practice: 1) only limited labeled sa…
Aggregated Gradient Langevin Dynamics
Chao Zhang, Jiahao Xie, Zebang Shen +3
In this paper, we explore a general Aggregated Gradient Langevin Dynamics framework (AGLD) for the Markov Chain Monte Carlo (MCMC) sampling. We investigate the nonasymptotic conver…
NAT: Neural Architecture Transformer for Accurate and Compact Architectures
Yong Guo, Yin Zheng, Mingkui Tan +4
Designing effective architectures is one of the key factors behind the success of deep neural networks. Existing deep architectures are either manually designed or automatically se…
Transferable Neural Processes for Hyperparameter Optimization
Ying Wei, Peilin Zhao, Huaxiu Yao +1
Automated machine learning aims to automate the whole process of machine learning, including model configuration. In this paper, we focus on automated hyperparameter optimization (…
Graph Convolutional Networks for Temporal Action Localization
Runhao Zeng, Wenbing Huang, Mingkui Tan +4
Most state-of-the-art action localization systems process each action proposal individually, without explicitly exploiting their relations during learning. However, the relations b…
Decentralized Online Learning: Take Benefits from Others' Data without Sharing Your Own to Track Global Trend
Yawei Zhao, Chen Yu, Peilin Zhao +3
Decentralized Online Learning (online learning in decentralized networks) attracts more and more attention, since it is believed that Decentralized Online Learning can help the dat…