Deep Learning: Difference between revisions
| Line 509: | Line 509: | ||
<ref name="zhang2017understanding">Chiyuan Zhang, Samy Bengio, Moritz Hardt, Benjamin Recht, Oriol Vinyals (2017) Understanding deep learning requires rethinking generalization (ICLR 2017) [https://arxiv.org/abs/1611.03530 https://arxiv.org/abs/1611.03530]</ref> | <ref name="zhang2017understanding">Chiyuan Zhang, Samy Bengio, Moritz Hardt, Benjamin Recht, Oriol Vinyals (2017) Understanding deep learning requires rethinking generalization (ICLR 2017) [https://arxiv.org/abs/1611.03530 https://arxiv.org/abs/1611.03530]</ref> | ||
<ref name="belkin2019reconciling">Mikhail Belkin, Daniel Hsu, Siyuan Ma, Soumik Mandal (2019) Reconciling modern machine learning practice and the bias-variance trade-off (PNAS 2019) [https://arxiv.org/abs/1812.11118 https://arxiv.org/abs/1812.11118]</ref> | <ref name="belkin2019reconciling">Mikhail Belkin, Daniel Hsu, Siyuan Ma, Soumik Mandal (2019) Reconciling modern machine learning practice and the bias-variance trade-off (PNAS 2019) [https://arxiv.org/abs/1812.11118 https://arxiv.org/abs/1812.11118]</ref> | ||
<ref name="jiang2019generalization">Yiding Jiang, Behnam Neyshabur, Hossein Mobahi, Dilip Krishnan, Samy Bengio (2019) Fantastic Generalization Measures and Where to Find Them [https://arxiv.org/abs/1912.02178 https://arxiv.org/abs/1912.02178]</ref> | |||
}} | }} | ||