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Machine learning models based on neural networks (NNs) are enjoying ever-increasing attention in the DB community.
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Chongyu Fan, Jiancheng Liu, Yihua Zhang, Dennis Wei, Eric Wong, and Sijia Liu. 2023 · 2023
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Fast Machine Unlearning Without Retraining Through Selective Synaptic Dampening
Jack Foster, Stefan Schoepf, and Alexandra Brintrup. 2023 · 2023
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Model Sparsity Can Simplify Machine Unlearning. In Annual Conference on Neural Information Processing Systems
Jinghan Jia, Jiancheng Liu, Parikshit Ram, Yuguang Yao, Gaowen Liu, Yang Liu, Pranay Sharma, and Sijia Liu. 2023 · 2023
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Detect, Distill and Update: Learned DB Systems Facing Out of Distribution Data. In Proceedings of the 2023 International Conference on Management of Data (to appear)
Meghdad Kurmanji and Peter Triantafillou. 2023 · 2023
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Towards Unbounded Machine Unlearning
Meghdad Kurmanji, Peter Triantafillou, Jamie Hayes, and Eleni Triantafillou. 2023 · 2023
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Jiaeli Shi, Najah Ghalyan, Kostis Gourgoulias, John Buford, and Sean Moran. 2023 · 2023
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FactorJoin: A New Cardinality Estimation Framework for Join Queries
Ziniu Wu, Parimarjan Negi, Alizadeh Mohammad, Tim Kraska, and Madden Samuel. 2023 · 2023
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