output
20122026
most citedSimple and Deep Graph Convolutional Networks

402 citations

Showing 2022Show all

14 papers · 1 filter

cs.CL2022★ 3 cited

Hybrid-Regressive Neural Machine Translation

Qiang Wang, Xinhui Hu, Ming Chen

In this work, we empirically confirm that non-autoregressive translation with an iterative refinement mechanism (IR-NAT) suffers from poor acceleration robustness because it is mor…

cs.LG2022★ 125 cited

TFAD: A Decomposition Time Series Anomaly Detection Architecture with Time-Frequency Analysis

Chaoli Zhang, Tian Zhou, Qingsong Wen +1

Time series anomaly detection is a challenging problem due to the complex temporal dependencies and the limited label data. Although some algorithms including both traditional and…

cs.CV2022★ 12 cited

DARTSRepair: Core-failure-set Guided DARTS for Network Robustness to Common Corruptions

Xuhong Ren, Jianlang Chen, Felix Juefei-Xu +5

Network architecture search (NAS), in particular the differentiable architecture search (DARTS) method, has shown a great power to learn excellent model architectures on the specif…

cs.DB2022★ 12 cited

Fine-Grained Modeling and Optimization for Intelligent Resource Management in Big Data Processing

Chenghao Lyu, Qi Fan, Fei Song +8

Big data processing at the production scale presents a highly complex environment for resource optimization (RO), a problem crucial for meeting performance goals and budgetary cons…

cs.DC2022★ 28 cited

Towards Transmission-Friendly and Robust CNN Models over Cloud and Device

Chuntao Ding, Zhichao Lu, Felix Juefei-Xu +3

Deploying deep convolutional neural network (CNN) models on ubiquitous Internet of Things (IoT) devices has attracted much attention from industry and academia since it greatly fac…

cs.CR2022★ 30 cited

A Customized Text Sanitization Mechanism with Differential Privacy

Huimin Chen, Fengran Mo, Yanhao Wang +4

As privacy issues are receiving increasing attention within the Natural Language Processing (NLP) community, numerous methods have been proposed to sanitize texts subject to differ…