From 5ebc60d023548ed70bab8d00eb021c820b5ee304 Mon Sep 17 00:00:00 2001
From: ak <alexander.krawczyk@informatik.hs-fulda.de>
Date: Thu, 23 Nov 2023 12:24:04 +0100
Subject: [PATCH] added big table
---
iclr2024_conference.tex | 707 +++++++++++++++++++++++++++++++++-------
1 file changed, 584 insertions(+), 123 deletions(-)
diff --git a/iclr2024_conference.tex b/iclr2024_conference.tex
index 0fe5e7c..1e7e6d0 100644
--- a/iclr2024_conference.tex
+++ b/iclr2024_conference.tex
@@ -183,7 +183,7 @@
\subsection{Adiabatic replay (AR)}
% TODO: "as a generator as well as a feature generator for the solver" könnte etwas unklar sein!
In contrast to conventional replay, where a scholar is composed of a generator and a solver network, see \cref{fig:genrep}, AR proposes scholars where a single network acts as a generator as well as a feature generator for the solver.
- Assuming a suitable scholar (see below), the high-level logic of AR is shown in \cref{fig:var}: Each sample from a new task is used to \textit{query} the scholar, which generates a similar, known sample. Mixing new and generated samples in a defined, constant proportion creates the training data for the current task (see \cref{alg:two} for pseudocode}).
+ Assuming a suitable scholar (see below), the high-level logic of AR is shown in \cref{fig:var}: Each sample from a new task is used to \textit{query} the scholar, which generates a similar, known sample. Mixing new and generated samples in a defined, constant proportion creates the training data for the current task (see \cref{alg:two} for pseudocode).
A new sample will cause adaptation of the scholar in a localized region of data space. Variants generated by that sample will, due to similarity, cause adaptation in the same region. Knowledge in the overlap region will therefore be adapted to represent both, while dissimilar regions stay unaffected (see \cref{fig:var} for a visual impression).
None of these requirements are fulfilled by DNNs, which is why we implement the scholar by a \enquote{flat} GMM layer (generator/feature encoder) followed by a linear classifier (solver). Both are independently trained via SGD according to \cite{gepperth2021gradient}. Extensions to deep convolutional GMMs (DCGMMs) \cite{gepperth2021new} for higher sampling capacity can be incorporated as drop-in replacements for the generator.
@@ -346,131 +346,592 @@
Results are tabulated in \cref{tab:short_results}.
%
\begin{table}[h!]
- \scriptsize
+ \scriptsize
%\footnotesize
\centering
\setlength\tabcolsep{1.5pt}
\begin{center}
- \begin{tabular}{ll:ccc:ccc|ccc:ccc|ccc:ccc|ccc:ccc}
- \multirow[c]{2}{*}[0in] & CIL-P & \multicolumn{6}{:c|}{D5-$1^5$A } & \multicolumn{6}{c|}{D5-$1^5$B} & \multicolumn{6}{c|}{D7-$1^3$A} & \multicolumn{6}{c}{D7-$1^3$B} \\[1pt]
+ \begin{tabular}{ll|ccccccccccccccccccccccccc}
+ % HEADER FIRST ROW
+ \multirow[c]{2}{*}[0in] & \multicolumn{1}{c|}{CIL-P}
+ & \multicolumn{12}{c}{D7-$1^5$A } & \multicolumn{12}{c}{D7-$1^5$B} \\[1pt]
+ \hline
+ % HEADER SECOND ROW
\multirow[c]{2}{*}[0in] & {\scriptsize measure} &
- \multicolumn{3}{c|}{$\alpha_T$} & \multicolumn{3}{c|}{$F_T$} & \multicolumn{3}{c|}{$\alpha_T$} & \multicolumn{3}{c|}{$F_T$} &
- \multicolumn{3}{c|}{$\alpha_T$} & \multicolumn{3}{c|}{$F_T$} & \multicolumn{3}{c|}{$\alpha_T$} & \multicolumn{3}{c}{$F_T$} \\[1pt]
- & method & AR & DGR & ER & AR & DGR & ER & AR & DGR & ER & AR & DGR & ER & AR & DGR & ER & AR & DGR & ER & AR & DGR & ER & AR & DGR & ER \\[1.5pt]
- \hline\hline
- & & & & & & & & & & & & & & & & & & & & & & \\
- \multirow[c]{5}{*}[0in]{\rotatebox{90}{DS}} & {\scriptsize MNIST} &
- .70 & .63 & \textbf{.75} &
- \textbf{.07} & .25 & .15 &
-
- .80 & .70 & \textbf{.89} &
- \textbf{.02} & .15 & .10 &
-
- .81 & .75 & \textbf{.90} &
- \textbf{.06} & .16 & .13 &
-
- .87 & .82 & \textbf{.92} &
- \textbf{.01} & .08 & .05
+ \multicolumn{6}{c:}{$\alpha_T$} & \multicolumn{6}{c:}{$F_T$} & \multicolumn{6}{c:}{$\alpha_T$} & \multicolumn{6}{c}{$F_T$} \\[1pt]
+ % HEADER THIRD ROW
+ & method
+ & \multicolumn{1}{c}{AR} & \multicolumn{2}{c}{ER} & \multicolumn{3}{c:}{DGR}
+ & \multicolumn{1}{c}{AR} & \multicolumn{2}{c}{ER} & \multicolumn{3}{c:}{DGR}
+ & \multicolumn{1}{c}{AR} & \multicolumn{2}{c}{ER} & \multicolumn{3}{c:}{DGR}
+ & \multicolumn{1}{c}{AR} & \multicolumn{2}{c}{ER} & \multicolumn{3}{c}{DGR} \\[1.5pt]
+ % HEADER FOURTH ROW
+ & scenario
+ & \multicolumn{1}{c}{b.} & \multicolumn{1}{c}{c.} & \multicolumn{1}{c}{w.} & \multicolumn{1}{c}{b.} & \multicolumn{1}{c}{c.} & \multicolumn{1}{c:}{w.}
+ & \multicolumn{1}{c}{b.} & \multicolumn{1}{c}{c.} & \multicolumn{1}{c}{w.} & \multicolumn{1}{c}{b.} & \multicolumn{1}{c}{c.} & \multicolumn{1}{c:}{w.}
+ & \multicolumn{1}{c}{b.} & \multicolumn{1}{c}{c.} & \multicolumn{1}{c}{w.} & \multicolumn{1}{c}{b.} & \multicolumn{1}{c}{c.} & \multicolumn{1}{c:}{w.}
+ & \multicolumn{1}{c}{b.} & \multicolumn{1}{c}{c.} & \multicolumn{1}{c}{w.} & \multicolumn{1}{c}{b.} & \multicolumn{1}{c}{c.} & \multicolumn{1}{c}{w.} \\[2pt]
+ \hline
+ %& & & & & & & & & & & & & & & & & & & & & & \\
+ \multirow[c]{5}{*}[0in]{\rotatebox{90}{DS}}
+ % --------------------> MNIST
+ & {\scriptsize MNIST}
+ % ACCURACY A
+ % AR - b.
+ & .81
+ % ER - c. / w.
+ & .90 & .93
+ % DGR - b. / c. / w.
+ & .96 & .75 & \multicolumn{1}{c:}{.93}
+
+ % FORGETTING A
+ % AR - b.
+ & .06
+ % ER - c. / w.
+ & .13 & .08
+ % DGR - b. / c. / w.
+ & .02 & .16 & \multicolumn{1}{c:}{.03}
+
+ % ACCURACY B
+ % AR - b.
+ & .87
+ % ER - c. / w.
+ & .92 & .95
+ % DGR - b. / c. / w.
+ & .97 & .82 & \multicolumn{1}{c:}{.97}
+
+ % FORGETTING B
+ % AR - b.
+ & .01
+ % ER - c. / w.
+ & .05 & .03
+ % DGR - b. / c. / w.
+ & .02 & .08 & \multicolumn{1}{c}{.02}
+ % --------------------> F-MNIST
\\
- % CONST./BALANCED
- % \textbf{.07} & .25/.13 & .15 &
- % .70 & .63/.83 & \textbf{.75} &
- % \textbf{.02} & .15/.06 & .10 &
- % .80 & .70/.90 & \textbf{.89} &
- % \textbf{.06} & .16/.10 & .13 &
- % .81 & .75/.90 & \textbf{.90} &
- % \textbf{.01} & .08/.02 & .05 &
- % .87 & .82/.90 & \textbf{.92} \\
- & {\scriptsize F-MNIST} &
- .70 & .63 & \textbf{.75} &
- \textbf{.16} & .71 & .31 &
-
- \textbf{.71} & .56 & \textbf{.71} &
- \textbf{.17} & .42 & .36 &
-
- .75 & .69 & \textbf{.79} &
- \textbf{.06} & .16 & .16 &
-
- \textbf{.73} & .66 & .71 &
- \textbf{.05} & .08 & .23
+ & {\scriptsize F-MNIST}
+ % ACCURACY A
+ % AR - b.
+ & .75
+ % ER - c. / w.
+ & .79 & .78
+ % DGR - b. / c. / w.
+ & .79 & .69 & \multicolumn{1}{c:}{.75}
+
+ % FORGETTING A
+ % AR - b.
+ & .06
+ % ER - c. / w.
+ & .16 & .16
+ % DGR - b. / c. / w.
+ & .08 & .16 & \multicolumn{1}{c:}{.07}
+
+ % ACCURACY B
+ % AR - b.
+ & .73
+ % ER - c. / w.
+ & .71 & .72
+ % DGR - b. / c. / w.
+ & .72 & .66 & \multicolumn{1}{c:}{.76}
+
+ % FORGETTING B
+ % AR - b.
+ & .05
+ % ER - c. / w.
+ & .23 & .25
+ % DGR - b. / c. / w.
+ & .17 & .08 & \multicolumn{1}{c}{.16}
+ % --------------------> FRUITS
\\
- % CONST./BALANCED
- % \textbf{.16} & .71/.34 & .31 &
- % .70 & .63/.77 & \textbf{.75} &
- % \textbf{.17} & .42/.34 & .36 &
- % .71 & .56/\textbf{.72} & .71 &
- % \textbf{.06} & .16/.10 & .16 &
- % .75 & .69/.80 & \textbf{.79} &
- % .05 & .08/\textbf{.02} & .23 &
- % \textbf{.73} & .66/.75 & .71 \\
- & {\scriptsize FRUITS} &
- .93 & .40 & \textbf{.99} &
- .11 & .22 & \textbf{.03} &
-
- .82 & .44 & \textbf{.99} &
- .13 & .21 & \textbf{.01} &
-
- .93 & .50 & \textbf{.98} &
- \textbf{.01} & .40 & .02 &
-
- .88 & .58 & \textbf{.98} &
- .15 & .23 & \textbf{.02}
+ & {\scriptsize FRUITS}
+ % ACCURACY A
+ % AR - b.
+ & .93
+ % ER - c. / w.
+ & .98 & .98
+ % DGR - b. / c. / w.
+ & .94 & .50 & \multicolumn{1}{c:}{.82}
+
+ % FORGETTING A
+ % AR - b.
+ & .01
+ % ER - c. / w.
+ & .02 & .01
+ % DGR - b. / c. / w.
+ & .02 & .40 & \multicolumn{1}{c:}{.06}
+
+ % ACCURACY B
+ % AR - b.
+ & .88
+ % ER - c. / w.
+ & .98 & .96
+ % DGR - b. / c. / w.
+ & .88 & .58 & \multicolumn{1}{c:}{.94}
+
+ % FORGETTING B
+ % AR - b.
+ & .15
+ % ER - c. / w.
+ & .02 & .03
+ % DGR - b. / c. / w.
+ & .09 & .23 & \multicolumn{1}{c}{.05}
+ % --------------------> SVHN
+ \\
+ & {\scriptsize SVHN}
+ % ACCURACY A
+ % AR - b.
+ & .92
+ % ER - c. / w.
+ & .73 & .78
+ % DGR - b. / c. / w.
+ & .31 & .33 & \multicolumn{1}{c:}{.34}
+
+ % FORGETTING A
+ % AR - b.
+ & .01
+ % ER - c. / w.
+ & .16 & .11
+ % DGR - b. / c. / w.
+ & .39 & .39 & \multicolumn{1}{c:}{.37}
+
+ % ACCURACY B
+ % AR - b.
+ & .93
+ % ER - c. / w.
+ & .81 & .81
+ % DGR - b. / c. / w.
+ & .23 & .25 & \multicolumn{1}{c:}{.28}
+
+ % FORGETTING B
+ % AR - b.
+ & .01
+ % ER - c. / w.
+ & .18 & .14
+ % DGR - b. / c. / w.
+ & .45 & .46 & \multicolumn{1}{c}{.45}
+ % --------------------> CIFAR-10
+ \\
+ & {\scriptsize CIFAR-10 }
+ % ACCURACY A
+ % AR - b.
+ & .72
+ % ER - c. / w.
+ & .60 & .60
+ % DGR - b. / c. / w.
+ & .27 & .25 & \multicolumn{1}{c:}{.28}
+
+ % FORGETTING A
+ % AR - b.
+ & .03
+ % ER - c. / w.
+ & .19 & .14
+ % DGR - b. / c. / w.
+ & .30 & .29 & \multicolumn{1}{c:}{.28}
+
+ % ACCURACY B
+ % AR - b.
+ & .70
+ % ER - c. / w.
+ & .62 & .62
+ % DGR - b. / c. / w.
+ & .30 & .32 & \multicolumn{1}{c:}{.31}
+
+ % FORGETTING B
+ % AR - b.
+ & .08
+ % ER - c. / w.
+ & .22 & .25
+ % DGR - b. / c. / w.
+ & .39 & .29 & \multicolumn{1}{c}{.38}
+ \\
+ \\
+ \multirow[c]{2}{*}[0in] & ...
+ & \multicolumn{12}{c}{D5-$1^5$A } & \multicolumn{12}{c}{D5-$1^5$B} \\[2pt]
+ \hline
+ %& & & & & & & & & & & & & & & & & & & & & & \\
+ % --------------------> MNIST
+ & {\scriptsize MNIST}
+ % ACCURACY A
+ % AR - b.
+ & .70
+ % ER - c. / w.
+ & .75 & .93
+ % DGR - b. / c. / w.
+ & .93 & .63 & \multicolumn{1}{c:}{.83}
+
+ % FORGETTING A
+ % AR - b.
+ & .07
+ % ER - c. / w.
+ & .15 & .12
+ % DGR - b. / c. / w.
+ & .05 & .25 & \multicolumn{1}{c:}{.08}
+
+ % ACCURACY B
+ % AR - b.
+ & .80
+ % ER - c. / w.
+ & .89 & .95
+ % DGR - b. / c. / w.
+ & .96 & .70 & \multicolumn{1}{c:}{.95}
+
+ % FORGETTING B
+ % AR - b.
+ & .02
+ % ER - c. / w.
+ & .10 & .07
+ % DGR - b. / c. / w.
+ & .04 & .15 & \multicolumn{1}{c}{.06}
+ % --------------------> F-MNIST
+ \\
+ & {\scriptsize F-MNIST}
+ % ACCURACY A
+ % AR - b.
+ & .70
+ % ER - c. / w.
+ & .75 & .75
+ % DGR - b. / c. / w.
+ & .78 & .63 & \multicolumn{1}{c:}{.68}
+
+ % FORGETTING A
+ % AR - b.
+ & .16
+ % ER - c. / w.
+ & .31 & .27
+ % DGR - b. / c. / w.
+ & .28 & .71 & \multicolumn{1}{c:}{.27}
+
+ % ACCURACY B
+ % AR - b.
+ & .71
+ % ER - c. / w.
+ & .71 & .70
+ % DGR - b. / c. / w.
+ & .61 & .56 & \multicolumn{1}{c:}{.63}
+
+ % FORGETTING B
+ % AR - b.
+ & .17
+ % ER - c. / w.
+ & .36 & .38
+ % DGR - b. / c. / w.
+ & .37 & .42 & \multicolumn{1}{c}{.33}
+ % --------------------> FRUITS
+ \\
+ & {\scriptsize FRUITS}
+ % ACCURACY A
+ % AR - b.
+ & .93
+ % ER - c. / w.
+ & .99 & .99
+ % DGR - b. / c. / w.
+ & .92 & .40 & \multicolumn{1}{c:}{.48}
+
+ % FORGETTING A
+ % AR - b.
+ & .11
+ % ER - c. / w.
+ & .03 & .05
+ % DGR - b. / c. / w.
+ & .09 & .22 & \multicolumn{1}{c:}{.20}
+
+ % ACCURACY B
+ % AR - b.
+ & .82
+ % ER - c. / w.
+ & .99 & .98
+ % DGR - b. / c. / w.
+ & .92 & .44 & \multicolumn{1}{c:}{.81}
+
+ % FORGETTING B
+ % AR - b.
+ & .13
+ % ER - c. / w.
+ & .01 & .02
+ % DGR - b. // w. / c.
+ & .07 & .21 & \multicolumn{1}{c}{.19}
+ % --------------------> SVHN
+ \\
+ & {\scriptsize SVHN}
+ % ACCURACY A
+ % AR - b.
+ & .92
+ % ER - c. / w.
+ & .69 & .73
+ % DGR - b. / c. / w.
+ & .29 & .32 & \multicolumn{1}{c:}{.38}
+
+ % FORGETTING A
+ % AR - b.
+ & .09
+ % ER - c. / w.
+ & .19 & .21
+ % DGR - b. / c. / w.
+ & .85 & .79 & \multicolumn{1}{c:}{.78}
+
+ % ACCURACY B
+ % AR - b.
+ & .92
+ % ER - c. / w.
+ & .76 & .77
+ % DGR - b. / c. / w.
+ & .34 & .37 & \multicolumn{1}{c:}{.43}
+
+ % FORGETTING B
+ % AR - b.
+ & .02
+ % ER - c. / w.
+ & .22 & .25
+ % DGR - b. / c. / w.
+ & .83 & .82 & \multicolumn{1}{c}{.82}
+ % --------------------> CIFAR-10
+ \\
+ & {\scriptsize CIFAR-10 }
+ % ACCURACY A
+ % AR - b.
+ & .73
+ % ER - c. / w.
+ & .59 & .57
+ % DGR - b. / c. / w.
+ & .30 & .29 & \multicolumn{1}{c:}{.31}
+
+ % FORGETTING A
+ % AR - b.
+ & .04
+ % ER - c. / w.
+ & .24 & .19
+ % DGR - b. / c. / w.
+ & .67 & .63 & \multicolumn{1}{c:}{.61}
+
+ % ACCURACY B
+ % AR - b.
+ & .71
+ % ER - c. / w.
+ & .63 & .62
+ % DGR - b. / c. / w.
+ & .31 & .29 & \multicolumn{1}{c:}{.32}
+
+ % FORGETTING B
+ % AR - b.
+ & .16
+ % ER - c. / w.
+ & .39 & .43
+ % DGR - b. / c. / w.
+ & .78 & .79 & \multicolumn{1}{c}{.77}
+ \\
+ \\
+ \multirow[c]{2}{*}[0in] & ...
+ & \multicolumn{12}{c}{D2-$2^5$A } & \multicolumn{12}{c}{D2-$2^5$B} \\[1pt]
+ \hline
+ %& & & & & & & & & & & & & & & & & & & & & & \\
+ % --------------------> MNIST
+ & {\scriptsize MNIST}
+ % ACCURACY A
+ % AR - b.
+ & .83
+ % ER - c. / w.
+ & .88 & .88
+ % DGR - b. / c. / w.
+ & .94 & .00 & \multicolumn{1}{c:}{.87}
+
+ % FORGETTING A
+ % AR - b.
+ & .03
+ % ER - c. / w.
+ & .12 & .15
+ % DGR - b. / c. / w.
+ & .05 & .00 & \multicolumn{1}{c:}{.09}
+
+ % ACCURACY B
+ % AR - b.
+ & .73
+ % ER - c. / w.
+ & .96 & .96
+ % DGR - b. / c. / w.
+ & .97 & .00 & \multicolumn{1}{c:}{.97}
+
+ % FORGETTING B
+ % AR - b.
+ & .02
+ % ER - c. / w.
+ & .14 & .10
+ % DGR - b. / c. / w.
+ & .06 & .00 & \multicolumn{1}{c}{.08}
+ % --------------------> F-MNIST
+ \\
+ & {\scriptsize F-MNIST}
+ % ACCURACY A
+ % AR - b.
+ & .67
+ % ER - c. / w.
+ & .64 & .64
+ % DGR - b. / c. / w.
+ & .65 & .00 & \multicolumn{1}{c:}{.57}
+
+ % FORGETTING A
+ % AR - b.
+ & .23
+ % ER - c. / w.
+ & .67 & .61
+ % DGR - b. / c. / w.
+ & .56 & .00 & \multicolumn{1}{c:}{.51}
+
+ % ACCURACY B
+ % AR - b.
+ & .69
+ % ER - c. / w.
+ & .81 & .81
+ % DGR - b. / c. / w.
+ & .80 & .00 & \multicolumn{1}{c:}{.82}
+
+ % FORGETTING B
+ % AR - b.
+ & .21
+ % ER - c. / w.
+ & .31 & .32
+ % DGR - b. / c. / w.
+ & .23 & .00 & \multicolumn{1}{c}{.18}
+ % --------------------> FRUITS
+ \\
+ & {\scriptsize FRUITS}
+ % ACCURACY A
+ % AR - b.
+ & .68
+ % ER - c. / w.
+ & .81 & .97
+ % DGR - b. / c. / w.
+ & .85 & .00 & \multicolumn{1}{c:}{.71}
+
+ % FORGETTING A
+ % AR - b.
+ & .05
+ % ER - c. / w.
+ & .25 & .05
+ % DGR - b. / c. / w.
+ & .14 & .00 & \multicolumn{1}{c:}{.23}
+
+ % ACCURACY B
+ % AR - b.
+ & .87
+ % ER - c. / w.
+ & .95 & .96
+ % DGR - b. / c. / w.
+ & .93 & .00 & \multicolumn{1}{c:}{.96}
+
+ % FORGETTING B
+ % AR - b.
+ & .03
+ % ER - c. / w.
+ & .06 & .02
+ % DGR - b. / c. / w.
+ & .10 & .00 & \multicolumn{1}{c}{.09}
+ % --------------------> SVHN
+ \\
+ & {\scriptsize SVHN}
+ % ACCURACY A
+ % AR - b.
+ & .92
+ % ER - c. / w.
+ & .64 & .65
+ % DGR - b. / c. / w.
+ & .20 & .23 & \multicolumn{1}{c:}{.25}
+
+ % FORGETTING A
+ % AR - b.
+ & .01
+ % ER - c. / w.
+ & .25 & .27
+ % DGR - b. / c. / w.
+ & .88 & .91 & \multicolumn{1}{c:}{.88}
+
+ % ACCURACY B
+ % AR - b.
+ & .92
+ % ER - c. / w.
+ & .89 & .89
+ % DGR - b. / c. / w.
+ & .63 & .61 & \multicolumn{1}{c:}{.62}
+
+ % FORGETTING B
+ % AR - b.
+ & .04
+ % ER - c. / w.
+ & .29 & .32
+ % DGR - b. / c. / w.
+ & .91 & .93 & \multicolumn{1}{c}{.92}
+ % --------------------> CIFAR-10
+ \\
+ & {\scriptsize CIFAR-10 }
+ % ACCURACY A
+ % AR - b.
+ & .67
+ % ER - c. / w.
+ & .53 & .51
+ % DGR - b. / c. / w.
+ & .09 & .11 & \multicolumn{1}{c:}{.14}
+
+ % FORGETTING A
+ % AR - b.
+ & .20
+ % ER - c. / w.
+ & .42 & .35
+ % DGR - b. / c. / w.
+ & .79 & .75 & \multicolumn{1}{c:}{.71}
+
+ % ACCURACY B
+ % AR - b.
+ & .68
+ % ER - c. / w.
+ & .74 & .74
+ % DGR - b. / c. / w.
+ & .54 & .54 & \multicolumn{1}{c:}{.57}
+
+ % FORGETTING B
+ % AR - b.
+ & .15
+ % ER - c. / w.
+ & .38 & .39
+ % DGR - b. / c. / w.
+ & .86 & .84 & \multicolumn{1}{c}{.83}
+ \\
+ \\
+ \multirow[c]{2}{*}[0in] & ...
+ & \multicolumn{12}{c}{D20-$1^5$A } & \multicolumn{12}{c}{D20-$1^5$B} \\[1pt]
+ \hline
+ %& & & & & & & & & & & & & & & & & & & & & & \\
+ & {\scriptsize E-MNIST }
+ % ACCURACY A
+ % AR - b.
+ & .61
+ % ER - c. / w.
+ & .73 & .66
+ % DGR - b. / c. / w.
+ & .65 & .25 & \multicolumn{1}{c:}{.00}
+
+ % FORGETTING A
+ % AR - b.
+ & .03
+ % ER - c. / w.
+ & .25 & .28
+ % DGR - b. / c. / w.
+ & .21 & .35 & \multicolumn{1}{c:}{.00}
+
+ % ACCURACY B
+ % AR - b.
+ & .59
+ % ER - c. / w.
+ & .75 & .80
+ % DGR - b. / c. / w.
+ & .77 & .24 & \multicolumn{1}{c:}{.00}
+
+ % FORGETTING B
+ % AR - b.
+ & .05
+ % ER - c. / w.
+ & .23 & .22
+ % DGR - b. / c. / w.
+ & .16 & .29 & \multicolumn{1}{c}{.00}
\\
- % CONST./BALANCED
- %.11 & .22/.11 & \textbf{.03} &
- %.93 & .40/.65 & \textbf{.99} &
- %.13 & .21/.07 & \textbf{.01} &
- %.82 & .44/.71 & \textbf{.99} &
- %\textbf{.01} & .40/.23 & .02 &
- %.93 & .50/.69 & \textbf{.98} &
- %.15 & .23/.15 & \textbf{.02} &
- %.88 & .58/.74 & \textbf{.98} \\
- & {\scriptsize SVHN} &
- \textbf{.92} & .06 & .69 &
- \textbf{.09} & .91 & .19 &
-
- \textbf{.92} & .08 & .76 &
- \textbf{.02} & .95 & .22 &
-
- \textbf{.92} & .19 & .73 &
- \textbf{.01} & .74 & .16 &
-
- \textbf{.93} & .18 & .81 &
- \textbf{.01} & .97 & .18 \\
- & {\scriptsize CIFAR-10 } &
- \textbf{.73} & .04 & .59 &
- \textbf{.04} & .95 & .24 &
-
- \textbf{.71} & .09 & .63 &
- \textbf{.16} & .96 & .39 &
-
- \textbf{.72} & .07 & .60 &
- \textbf{.03} & .87 & .19 &
-
- \textbf{.70} & .15 & .62 &
- \textbf{.08} & .89 & .22 \\
- \end{tabular}
- \end{center}
- \vspace{0.2cm}
- \begin{center}
- \begin{tabular}{l:ccc:ccc|ccc:ccc}
- CIL-P & \multicolumn{6}{c|}{D20-$1^5$A } & \multicolumn{6}{|c}{D20-$1^5$B} \\
- {\scriptsize measure} & \multicolumn{3}{c|}{$\alpha_T$} & \multicolumn{3}{c|}{$F_T$} &
- \multicolumn{3}{c|}{$\alpha_T$} & \multicolumn{3}{c}{$F_T$} \\[1pt]
- method & AR & DGR & ER & AR & DGR & ER & AR & DGR & ER & AR & DGR & ER \\
- \hline\hline
- & \multicolumn{3}{c:}{} & \multicolumn{3}{c|}{} & \multicolumn{3}{c:}{} & \multicolumn{3}{c}{} \\
- {\scriptsize E-MNIST } &
- % CONST./BALANCED
- % \textbf{.03} & .35/.31 & .25 &
- % .61 & .25/.74 & \textbf{.73} &
- % \textbf{.05} & .29/.34 & .23 &
- % .59 & .24/.72 & \textbf{.75}
- .61 & .25 & \textbf{.73} &
- \textbf{.03} & .35 & .25 &
-
- .59 & .24 & \textbf{.75} &
- \textbf{.05} & .29 & .23 \\
\end{tabular}
\end{center}
\vspace{0.2cm}
@@ -478,7 +939,7 @@
\begin{center}
\begin{tabular}{ll:c:c:c:c:c:c}
& \multicolumn{1}{l|}{DS} & \multicolumn{1}{l|}{MNIST} & \multicolumn{1}{l|}{F-MNIST} & \multicolumn{1}{l|}{E-MNIST} & \multicolumn{1}{l|}{FRUITS} & \multicolumn{1}{l|}{SVHN} & \multicolumn{1}{l}{CIFAR-10} \\[1pt]
- \hline\hline
+ \hline
& & & & & & & \\
\multirow[c]{2}{*}[0in]{\rotatebox{90}{method}} & AR & .92 & .78 & .67 & \textbf{.99} & .93 & .74 \\
%\cdashline{2-8}
@@ -486,10 +947,10 @@
& & & & & & & \\
\end{tabular}
\end{center}
- \caption{Main experimental results. The first and second table display the results of all investigated methods (AR, DGR and ER) for each class-incremental learning problem (CIL-P). We present the final test-set accuracy $\alpha_T$ and an average forgetting measure $F_T$ for each CIL-P.
- The relevant baselines $\alpha^\text{base}$ (joint-training) are showcased in the bottom table.
- All results are averaged across $N=10$ runs.
- Detailed information about the evaluation process and experimental setup can be found in \cref{sec:exppeval}.
+ \caption{Main experimental results. The main table displays the results of all investigated methods (AR, DGR and ER) for each class-incremental learning problem (CIL-P) under each imposed scenario (b. = balanced, c. = constant-time, w. = weighted sample loss). We present the final test-set accuracy $\alpha_T$ and an average forgetting measure $F_T$ for each CIL-P.
+ The relevant baselines $\alpha^\text{base}$ (joint-training) are showcased in the bottom table.
+ All results are averaged across $N=10$ runs.
+ Detailed information about the evaluation process and experimental setup can be found in \cref{sec:exppeval}.
\label{tab:short_results}}
\end{table}
%
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