Tvrelease Posted November 30, 2022 Report Share Posted November 30, 2022 [img]https://i.postimg.cc/KckVh2JQ/fb3f667e-e055-44a9-bd34-786410b51622.png[/img] English | 2022 | ISBN: 9811967024 | 92 Pages | PDF EPUB (True) | 23 MB Latent factor analysis models are an effective type of machine learning model for addressing high-dimensional and sparse matrices, which are encountered in many big-data-related industrial applications. The performance of a latent factor analysis model relies heavily on appropriate hyper-parameters. However, most hyper-parameters are data-dependent, and using grid-search to tune these hyper-parameters is truly laborious and expensive in computational terms. Hence, how to achieve efficient hyper-parameter adaptation for latent factor analysis models has become a significant question. [b]Download Links[/b] [b]Rapidgator[/b] [code] https://rapidgator.net/file/3ef6cfa08b8e9a7ab4c25458009baa5e/HkKrHOT7__Latent_Fac.rar.html [/code] [b]Nitroflare[/b] [code] https://nitroflare.com/view/74388C286A977D8/HkKrHOT7__Latent_Fac.rar[/code] Link to comment Share on other sites More sharing options...
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