Task Understanding from Confushing Multitask Data: Difference between revisions
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=Experiment= | =Experiment= | ||
==Setup== | ==Setup== | ||
Confusing data comes in the form of <math>(x_i,y_i),i=1,...,m<math> pairs. However, unlike typical regression problems, there are multiple <math>f_j(x),j=1,...,n<math> mapping functions, so the goal is to recover both the mapping functions <math>f_j<math> as well as determine which mapping function corresponds to each of the <math>m<math> observations. | Confusing data comes in the form of <math>(x_i,y_i),i=1,...,m<\math> pairs. However, unlike typical regression problems, there are multiple <math>f_j(x),j=1,...,n<\math> mapping functions, so the goal is to recover both the mapping functions <math>f_j<\math> as well as determine which mapping function corresponds to each of the <math>m<math> observations. | ||
Revision as of 16:20, 15 November 2020
Task Understanding from Confusing Multi-task Data
Presented By aslkdfj;awekrf
1. Introduction
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Hello
[math]\displaystyle{ \begin{align*} e & = \pi = \sqrt{g} \end{align*} }[/math]
2. Related Work
How does formatting of paragraphs work? hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi hi
[math]\displaystyle{ \begin{align*} e & = \text{Hellow}\\ & = \dfrac{123}{4}\\ \end{align*} }[/math]
[math]\displaystyle{
\begin{align*}
h+1 & = \dfrac{abc}{\text{def}}\\
& = \dfrac{123}{4}\\
\end{align*}
}[/math]
Experiment
Setup
Confusing data comes in the form of <math>(x_i,y_i),i=1,...,m<\math> pairs. However, unlike typical regression problems, there are multiple <math>f_j(x),j=1,...,n<\math> mapping functions, so the goal is to recover both the mapping functions <math>f_j<\math> as well as determine which mapping function corresponds to each of the <math>m<math> observations.