From 0acd8ff84a78e0ed0ab106889b24ce04db321cef Mon Sep 17 00:00:00 2001 From: lukas-heilgenbrunner Date: Wed, 3 May 2023 16:04:46 +0200 Subject: [PATCH] write introduction --- summary/main.tex | 49 +++++++++++++++------------------------------ summary/sources.bib | 2 +- 2 files changed, 17 insertions(+), 34 deletions(-) diff --git a/summary/main.tex b/summary/main.tex index ee3e64e..718f0ba 100644 --- a/summary/main.tex +++ b/summary/main.tex @@ -89,53 +89,36 @@ \maketitle \section{Introduction} -ACM's consolidated article template, introduced in 2017, provides a -consistent \LaTeX\ style for use across ACM publications, and -incorporates accessibility and metadata-extraction functionality -necessary for future Digital Library endeavors. Numerous ACM and -SIG-specific \LaTeX\ templates have been examined, and their unique -features incorporated into this single new template. +For most supervised learning tasks are lots of training samples essential. +with too less training data the model will gerneralize not well and not fit a real world task. +Labeling datasets is in commonly seen as an expensive task and wants to be avoided as much as possible. +Thats why there is a machine-learning field called Semi-Supervised learning. +The general approach is to train a model that predicts Pseudo-Labels which then can be used to train the main model. -If you are new to publishing with ACM, this document is a valuable -guide to the process of preparing your work for publication. If you -have published with ACM before, this document provides insight and -instruction into more recent changes to the article template. +\section{Semi-Supervised learning} +todo write stuff -The ``\verb|acmart|'' document class can be used to prepare articles -for any ACM publication --- conference or journal, and for any stage -of publication, from review to final ``camera-ready'' copy, to the -author's own version, with {\itshape very} few changes to the source. +\section{FixMatch}\label{sec:fixmatch} +There exists an already existing approach called FixMatch. +This was introduced in a Google Research paper from 2020~\cite{fixmatch}. + +\section{Cross-Model Pseudo-Labeling} +todo write stuff \cite{Xu_2022_CVPR} \section{Math}\label{sec:math} \begin{equation} \label{eq:equation} \mathcal{L}_u = \frac{1}{B_u} \sum_{i=1}^{B_u} \mathbbm{1}(\max(p_i) \geq \tau) \mathcal{H}(\hat{y}_i,F(\mathcal{T}_{\text{strong}}(u_i))) \end{equation} -As noted in the introduction, the ``\verb|acmart|'' document class can -be used to prepare many different kinds of documentation --- a -double-blind initial submission of a full-length technical paper, a -two-page SIGGRAPH Emerging Technologies abstract, a ``camera-ready'' -journal article, a SIGCHI Extended Abstract, and more --- all by -selecting the appropriate {\itshape template style} and {\itshape - template parameters}. - -This document will explain the major features of the document -class. For further information, the {\itshape \LaTeX\ User's Guide} is -available from -\url{https://www.acm.org/publications/proceedings-template}. \section{Figures} -\cite{Xu_2022_CVPR} -\cite{knuthwebsite} - \begin{figure}[h] \centering \includegraphics[width=\linewidth]{../presentation/rsc/results} - \caption{1907 Franklin Model D roadster. Photograph by Harris \& - Ewing, Inc. [Public domain], via Wikimedia - Commons. (\url{https://goo.gl/VLCRBB}).} - \Description{A woman and a girl in white dresses sit in an open car.}\label{fig:figure} + \caption{Performance comparisons between CMPL, FixMatch and supervised learning only} + \Description{A woman and a girl in white dresses sit in an open car.} + \label{fig:results} \end{figure} %% diff --git a/summary/sources.bib b/summary/sources.bib index 0791896..c80818e 100644 --- a/summary/sources.bib +++ b/summary/sources.bib @@ -7,7 +7,7 @@ pages = {2959-2968} } -@online{knuthwebsite, +@online{fixmatch, author = "Kihyuk Sohn, David Berthelot, Chun-Liang Li", title = "FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence", url = "https://arxiv.org/abs/2001.07685",