activity
20152026
most citedFederated Learning with Non-IID Data

1.9k citations · 2.1k across the 43 of their papers we have counts for

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Showing 2018Show all

7 papers · 1 filter

cs.CV2018

Automated segmentaiton and classification of arterioles and venules using Cascading Dilated Convolutional Neural Networks

Meng Li, Yan Zhang, Haicheng She +4

The change of retinal vasculature is an early sign of many vascular and systematic diseases, such as diabetes and hypertension. Different behaviors of retinal arterioles and venule…

cs.LG2018★ 10 cited

Multistep Speed Prediction on Traffic Networks: A Graph Convolutional Sequence-to-Sequence Learning Approach with Attention Mechanism

Zhengchao Zhang, Meng Li, Xi Lin +2

Multistep traffic forecasting on road networks is a crucial task in successful intelligent transportation system applications. To capture the complex non-stationary temporal dynami…

cs.CG2018

Streaming Algorithms for Planar Convex Hulls

Martin Farach-Colton, Meng Li, Meng-Tsung Tsai

Many classical algorithms are known for computing the convex hull of a set of point in using space. For large point sets, whose size exceeds the size of t…

cs.CV2018★ 5 cited

Computed Tomography Image Enhancement using 3D Convolutional Neural Network

Meng Li, Shiwen Shen, Wen Gao +2

Computed tomography (CT) is increasingly being used for cancer screening, such as early detection of lung cancer. However, CT studies have varying pixel spacing due to differences…

cs.LG2018★ 6 cited

Data Efficient Lithography Modeling with Transfer Learning and Active Data Selection

Yibo Lin, Meng Li, Yuki Watanabe +4

Lithography simulation is one of the key steps in physical verification, enabled by the substantial optical and resist models. A resist model bridges the aerial image simulation to…

cs.LG2018★ 1.9k cited

Federated Learning with Non-IID Data

Yue Zhao, Meng Li, Liangzhen Lai +3

Federated learning enables resource-constrained edge compute devices, such as mobile phones and IoT devices, to learn a shared model for prediction, while keeping the training data…