ゼロから始める深層強化学習(NLP2018講演資料)/ Introduction of Deep Reinforcement LearningPreferred Networks
Introduction of Deep Reinforcement Learning, which was presented at domestic NLP conference.
言語処理学会第24回年次大会(NLP2018) での講演資料です。
http://www.anlp.jp/nlp2018/#tutorial
Computing for Isogeny Kernel Problem by Groebner BasisYasu Math
Today, Tani's Claw finding algorithm is the fastest method of isogeny kernel problem. However, We don't use the property of elliptic curves and isogeny to solve the problem by Tani's algorithm. We suggest new method of computing for isogeny kernel problem by Velu's formula and Groebner basis.
ゼロから始める深層強化学習(NLP2018講演資料)/ Introduction of Deep Reinforcement LearningPreferred Networks
Introduction of Deep Reinforcement Learning, which was presented at domestic NLP conference.
言語処理学会第24回年次大会(NLP2018) での講演資料です。
http://www.anlp.jp/nlp2018/#tutorial
Computing for Isogeny Kernel Problem by Groebner BasisYasu Math
Today, Tani's Claw finding algorithm is the fastest method of isogeny kernel problem. However, We don't use the property of elliptic curves and isogeny to solve the problem by Tani's algorithm. We suggest new method of computing for isogeny kernel problem by Velu's formula and Groebner basis.