problem formulation

finetuning.tex

-\begin{minipage}[c]{0.55\textwidth}
-  \textbf{Setting:}
+\vspace{0.45cm}
+\begin{minipage}[c]{0.46\textwidth}
+  \textbf{Problem Formulation:}
   \begin{itemize}
-  \item classes appear sequentially (or in batches) % $c_1,c_2,\dots,c_T$
-  \item each class $y$ has training images $X^y=\{x^y_1,\dots,x^y_{n_y}\}$
-  \end{itemize}
+  \item Pretrained model $M$ for task $T: X \rightarrow Y$
+  \item How to most efficiently fine-tune $M$ for new task $T': X' \rightarrow Y$ where $\mathcal{P}(X) \neq \mathcal{P}(X')$
+  \item \textbf{Baseline:} Fine-tuning 
+    \begin{itemize}
+      \item slow for large models 
+        \item  overfitting (small $X'$, many parameters)
+        \end{itemize}
+      \end{itemize}
 \end{minipage}
-~
-\begin{minipage}[c]{0.4\textwidth}
+%
+\begin{minipage}[c]{0.49\textwidth}
 \begin{center}
   \newcommand{\pacsheight}{2.5cm}
   \textbf{Example (PACS~\blue{[1]} dataset and variants)}
-  \begin{minipage}[c]{0.14\textwidth}
+  \begin{minipage}[c]{0.16\textwidth}
     \centering \includegraphics[height=\pacsheight]{pacs_1.png}
 
-    \centering \scriptsize Photo
-  \end{minipage}~
+    \centering \scriptsize \blue{Photo (base)}
+  \end{minipage}~~~
   \begin{minipage}[c]{0.14\textwidth}
     \centering \includegraphics[height=\pacsheight]{pacs_2.png}