Few-Shot Unlearning by Model Inversion

Autor: Yoon, Youngsik, Nam, Jinhwan, Yun, Hyojeong, Lee, Jaeho, Kim, Dongwoo, Ok, Jungseul

We consider a practical scenario of machine unlearning to erase a target dataset, which causes unexpected behavior from the trained model. The target dataset is often assumed to be fully identifiable in a standard unlearning scenario. Such a flawless

Externí odkaz: http://arxiv.org/abs/2205.15567

Predicting Self-Heating Temperature and Influencing Factors in the Cement Composite Mixed with Multi-Walled Carbon Nanotubes Using Machine Learning.

Autor: Lee, Jaewon, Yun, Hyojeong, Cha, Yoonseon, Chung, Wonseok

Publikováno v: Sustainability (2071-1050); Dec2024, Vol. 16 Issue 23, p10420, 14p

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Anti-Fatigue Activity of a Mixture of Stauntonia hexaphylla (Thunb.) Decaisne and Vaccinium bracteatum Thunb. Fruit Extract.

Autor: Oh J; Herbal Hormone Research Institute, Naturalendo Tech Co., Ltd., Gyeonggi 13486, Korea., Han Y; Herbal Hormone Research Institute, Naturalendo Tech Co., Ltd., Gyeonggi 13486, Korea., Kim J; Herbal Hormone Research Institute, Naturalendo Tech Co., Ltd., Gyeonggi 13486, Korea., Park C; Herbal Hormone Research Institute, Naturalendo Tech Co., Ltd., Gyeonggi 13486, Korea., Oh D; Jeollanamdo Institute of Natural Resources Research, Jeonnam 59338, Korea., Yun H; Jeollanamdo Institute of Natural Resources Research, Jeonnam 59338, Korea., Lee G; Jeollanamdo Institute of Natural Resources Research, Jeonnam 59338, Korea., Kim J; Jeollanamdo Institute of Natural Resources Research, Jeonnam 59338, Korea., Choi C; Jeollanamdo Institute of Natural Resources Research, Jeonnam 59338, Korea., Lee Y; Herbal Hormone Research Institute, Naturalendo Tech Co., Ltd., Gyeonggi 13486, Korea.

Publikováno v: Preventive nutrition and food science [Prev Nutr Food Sci] 2020 Dec 31; Vol. 25 (4), pp. 380-388.