Mercurial > ift6266
comparison writeup/techreport.tex @ 461:9609c5cf9b6b
lit. results
author | Yoshua Bengio <bengioy@iro.umontreal.ca> |
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date | Fri, 28 May 2010 07:48:14 -0600 |
parents | fe292653a0f8 |
children | f59af1648d83 |
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460:fe292653a0f8 | 461:9609c5cf9b6b |
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378 (MLP=Multi-Layer Perceptron). The models shown are all trained using perturbed data (NISTP or P07) | 378 (MLP=Multi-Layer Perceptron). The models shown are all trained using perturbed data (NISTP or P07) |
379 and using a validation set to select hyper-parameters and other training choices. | 379 and using a validation set to select hyper-parameters and other training choices. |
380 \{SDA,MLP\}0 are trained on NIST, | 380 \{SDA,MLP\}0 are trained on NIST, |
381 \{SDA,MLP\}1 are trained on NISTP, and \{SDA,MLP\}2 are trained on P07. | 381 \{SDA,MLP\}1 are trained on NISTP, and \{SDA,MLP\}2 are trained on P07. |
382 The human error rate on digits is a lower bound because it does not count digits that were | 382 The human error rate on digits is a lower bound because it does not count digits that were |
383 recognized as letters.} | 383 recognized as letters. For comparison, the results found in the literature |
384 on NIST digits classification using the same test set are included.} | |
384 \label{tab:sda-vs-mlp-vs-humans} | 385 \label{tab:sda-vs-mlp-vs-humans} |
385 \begin{center} | 386 \begin{center} |
386 \begin{tabular}{|l|r|r|r|r|} \hline | 387 \begin{tabular}{|l|r|r|r|r|} \hline |
387 & NIST test & NISTP test & P07 test & NIST test digits \\ \hline | 388 & NIST test & NISTP test & P07 test & NIST test digits \\ \hline |
388 Humans& 18.2\% $\pm$.1\% & 39.4\%$\pm$.1\% & 46.9\%$\pm$.1\% & $>1.1\%$ \\ \hline | 389 Humans& 18.2\% $\pm$.1\% & 39.4\%$\pm$.1\% & 46.9\%$\pm$.1\% & $>1.1\%$ \\ \hline |
390 SDA1 & 17.1\% $\pm$.13\% & 29.7\%$\pm$.3\% & 29.7\%$\pm$.3\% & 1.4\% $\pm$.1\%\\ \hline | 391 SDA1 & 17.1\% $\pm$.13\% & 29.7\%$\pm$.3\% & 29.7\%$\pm$.3\% & 1.4\% $\pm$.1\%\\ \hline |
391 SDA2 & 18.7\% $\pm$.13\% & 33.6\%$\pm$.3\% & 39.9\%$\pm$.17\% & 1.7\% $\pm$.1\%\\ \hline | 392 SDA2 & 18.7\% $\pm$.13\% & 33.6\%$\pm$.3\% & 39.9\%$\pm$.17\% & 1.7\% $\pm$.1\%\\ \hline |
392 MLP0 & 24.2\% $\pm$.15\% & 68.8\%$\pm$.33\% & 78.70\%$\pm$.14\% & 3.45\% $\pm$.15\% \\ \hline | 393 MLP0 & 24.2\% $\pm$.15\% & 68.8\%$\pm$.33\% & 78.70\%$\pm$.14\% & 3.45\% $\pm$.15\% \\ \hline |
393 MLP1 & 23.0\% $\pm$.15\% & 41.8\%$\pm$.35\% & 90.4\%$\pm$.1\% & 3.85\% $\pm$.16\% \\ \hline | 394 MLP1 & 23.0\% $\pm$.15\% & 41.8\%$\pm$.35\% & 90.4\%$\pm$.1\% & 3.85\% $\pm$.16\% \\ \hline |
394 MLP2 & 24.3\% $\pm$.15\% & 46.0\%$\pm$.35\% & 54.7\%$\pm$.17\% & 4.85\% $\pm$.18\% \\ \hline | 395 MLP2 & 24.3\% $\pm$.15\% & 46.0\%$\pm$.35\% & 54.7\%$\pm$.17\% & 4.85\% $\pm$.18\% \\ \hline |
396 [5] & & & & 4.95\% $\pm$.18\% \\ \hline | |
397 [2] & & & & 3.71\% $\pm$.16\% \\ \hline | |
398 [3] & & & & 2.4\% $\pm$.13\% \\ \hline | |
399 [4] & & & & 2.1\% $\pm$.12\% \\ \hline | |
395 \end{tabular} | 400 \end{tabular} |
396 \end{center} | 401 \end{center} |
397 \end{table} | 402 \end{table} |
398 | 403 |
399 \subsection{Perturbed Training Data More Helpful for SDAE} | 404 \subsection{Perturbed Training Data More Helpful for SDAE} |