{Overleaf 模板库}LaTeX 模板 — Recent

山中 卓 (大阪大学 大学院理学研究科 物理学専攻)先生が作成された科研費LaTeXを、坂東 慶太 (名古屋学院大学) が了承を得てテンプレート登録しています。 詳細はこちら↓をご確認ください。 http://osksn2.hep.sci.osaka-u.ac.jp/~taku/kakenhiLaTeX/

山中 卓 (大阪大学 大学院理学研究科 物理学専攻)先生が作成された科研費LaTeXを、坂東 慶太 (名古屋学院大学) が了承を得てテンプレート登録しています。 詳細はこちら↓をご確認ください。 http://osksn2.hep.sci.osaka-u.ac.jp/~taku/kakenhiLaTeX/

Third Year (T.E.) Mini Project Report Template made by me for submission in case of SDL (SPPU B.E. 2015 Pat.)

Please follow the instructions given in the tex file seminar_report.tex This document contains essential templates required to write technical reports using LaTeX. This template may be used for the preparation of B.Tech seminar reports of APJ Abdul Kalam Technological University, Kerala. Also minimum working examples to create equations, include figure, include table, table of contents symbols list and bibliographic citation (using a bib file) in a Latex document are provided. Please note that this template is provided without warranty on an AS IS basis JIM

Plantilla de Tesis UDG, para la licenciatura en física

Model cards - https://arxiv.org/abs/1810.03993 Are "short documents accompanying trained machine learning models that provide benchmarked evaluation in a variety of conditions, such as across different cultural, demographic, or phenotypic groups... and intersectional groups... that are relevant to the intended application domains. Model cards also disclose the context in which models are intended to be used, details of the performance evaluation procedures, and other relevant information." Model cards were motivated by systematic bias in commercial applications that were discovered only after the models were released. To counter that, the authors "advocate for measures of model performance that contain quantitative evaluation results to be broken down by individual cultural, demographic, or phenotypic groups, domain-relevant conditions, and intersectional analysis combining two (or more) groups and conditions." The emphasis on ethical aspects of the measurements is a distinguishing feature of model cards, compared to other proposals to document models.

Datasheets for Datasets - https://arxiv.org/abs/1803.09010 "Document [the dataset] motivation, composition, collection process, recommended uses, and so on. [They] have the potential to increase transparency and accountability within the machine learning community, mitigate unwanted biases in machine learning systems, facilitate greater reproducibility of machine learning results, and help researchers and practitioners select more appropriate datasets for their chosen tasks.'' The motivation behind the proposal was the electronics industry, where every component has a datasheet that describes its operating characteristics and recommended uses. In machine learning, data is the input for model training. Using the wrong dataset, or using a dataset outside of its original intent, or even not understanding well enough the limitations of a dataset, has dire consequences for the model. However, ``[d]espite the importance of data to machine learning, there is no standardized process for documenting machine learning datasets. To address this gap, we propose datasheets for datasets.''

東京大学大学院情報理工学系研究科コンピュータ科学専攻 博士論文をを組版するためのドキュメントクラス iscs-thesis (v1.3) を Overleaf に対応させたものです。

東京大学大学院情報理工学系研究科コンピュータ科学専攻 修士論文を組版するためのドキュメントクラス iscs-thesis (v1.3) を Overleaf に対応させたものです。