539 citations · 1.1k across the 28 of their papers we have counts for
5 papers · 1 filter
Combinatorial Auctions and Graph Neural Networks for Local Energy Flexibility Markets
Awadelrahman M. A. Ahmed, Frank Eliassen, Yan Zhang
This paper proposes a new combinatorial auction framework for local energy flexibility markets, which addresses the issue of prosumers' inability to bundle multiple flexibility tim…
Balancing Explainability-Accuracy of Complex Models
Poushali Sengupta, Yan Zhang, Sabita Maharjan +1
Explainability of AI models is an important topic that can have a significant impact in all domains and applications from autonomous driving to healthcare. The existing approaches…
(Re)H2O: Autonomous Driving Scenario Generation via Reversely Regularized Hybrid Offline-and-Online Reinforcement Learning
Haoyi Niu, Kun Ren, Yizhou Xu +4
Autonomous driving and its widespread adoption have long held tremendous promise. Nevertheless, without a trustworthy and thorough testing procedure, not only does the industry str…
Explanation-based Counterfactual Retraining(XCR): A Calibration Method for Black-box Models
Liu Zhendong, Wenyu Jiang, Yi Zhang +1
With the rapid development of eXplainable Artificial Intelligence (XAI), a long line of past work has shown concerns about the Out-of-Distribution (OOD) problem in perturbation-bas…
Deep Anomaly Detection for Time-series Data in Industrial IoT: A Communication-Efficient On-device Federated Learning Approach
Yi Liu, Sahil Garg, Jiangtian Nie +4
Since edge device failures (i.e., anomalies) seriously affect the production of industrial products in Industrial IoT (IIoT), accurately and timely detecting anomalies is becoming…