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Proofs and additional experiments on Second order techniques for learning time-series with structural breaks

Osogami, Takayuki

arXiv.org Machine LearningDec-14-2020

We provide complete proofs of the lemmas about the properties of the regularized loss function that is used in the second order techniques for learning time-series with structural breaks in Osogami (2021). In addition, we show experimental results that support the validity of the techniques.

order order order 1, proposed 0, regularization, (12 more...)

arXiv.org Machine Learning

2012.08037

Country: Asia > Japan > Honshū > Kantō > Tokyo Metropolis Prefecture > Tokyo (0.04)

Genre: Research Report (0.82)

Technology: Information Technology > Artificial Intelligence (0.47)

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