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20162023
most citedDeepGauge: Multi-Granularity Testing Criteria for Deep Learning Systems

591 citations · 3.3k across the 128 of their papers we have counts for

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Showing 2020Show all

30 papers · 1 filter

eess.SY2020

A Gaussian Process-based Price-Amount Curve Construction for Demand Response Provided by Internet Data Centers

Yang Liu, Hung D. Nguyen

For a Demand Response (DR) program with internet data centers (IDC), the Price-Amount curve that estimates how the potential DR amount depends on the DR price determined by power s…

eess.SY2020

Gaussian Process-based Approach for Bilevel Optimization in the Power System -- A Critical Load Restoration Case

Yang Liu, Yu Weng, Rufan Yang +2

Bilevel optimization problems can be used to represent the collaborative interaction between a power system and grid-connected entities, called the followers, such as data centers.…

cs.CV2020★ 17 cited

EfficientDeRain: Learning Pixel-wise Dilation Filtering for High-Efficiency Single-Image Deraining

Qing Guo, Jingyang Sun, Felix Juefei-Xu +4

Single-image deraining is rather challenging due to the unknown rain model. Existing methods often make specific assumptions of the rain model, which can hardly cover many diverse…

cs.LG2020★ 29 cited

Privacy-Preserving Technology to Help Millions of People: Federated Prediction Model for Stroke Prevention

Ce Ju, Ruihui Zhao, Jichao Sun +11

Prevention of stroke with its associated risk factors has been one of the public health priorities worldwide. Emerging artificial intelligence technology is being increasingly adop…

eess.SY2020

Continuous Multiagent Control using Collective Behavior Entropy for Large-Scale Home Energy Management

Jianwen Sun, Yan Zheng, Jianye Hao +2

With the increasing popularity of electric vehicles, distributed energy generation and storage facilities in smart grid systems, an efficient Demand-Side Management (DSM) is urgent…

cs.CR2020★ 4 cited

Stealthy and Efficient Adversarial Attacks against Deep Reinforcement Learning

Jianwen Sun, Tianwei Zhang, Xiaofei Xie +4

Adversarial attacks against conventional Deep Learning (DL) systems and algorithms have been widely studied, and various defenses were proposed. However, the possibility and feasib…