most citedSelective Forgetting of Deep Networks at a Finer Level than Samples

2 citations · 2 across the 2 of their papers we have counts for

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2 papers

stat.ML2020★ 2 cited

Selective Forgetting of Deep Networks at a Finer Level than Samples

Tomohiro Hayase, Suguru Yasutomi, Takashi Katoh

Selective forgetting or removing information from deep neural networks (DNNs) is essential for continual learning and is challenging in controlling the DNNs. Such forgetting is cru…

cs.LG2018

Multi Instance Learning For Unbalanced Data

Mark Kozdoba, Edward Moroshko, Lior Shani +4

In the context of Multi Instance Learning, we analyze the Single Instance (SI) learning objective. We show that when the data is unbalanced and the family of classifiers is suffici…