Leverage top XAI frameworks to explain your machine learning models with ease and discover best practices and guidelines to build scalable explainable ML systems Key Features • Explore various expla……続きを見る
著者：Daniil Ryabko
出版社： Springer International Publishing
発売日： 2019年03月09日
Stationarity is a very general, qualitative assumption, that can be assessed on the basis of application specifics. It is thus a rather attractive assumption to base statistical analysis on, especia……続きを見る
著者：Lilya Budaghyan
出版社： Springer International Publishing
発売日： 2015年12月29日
This book covers novel research on construction and analysis of optimal cryptographic functions such as almost perfect nonlinear (APN), almost bent (AB), planar and bent functions. These functions h……続きを見る
