Regularization methods such as weight decay (-regularization) or sparsity (-regularization) can be applied during training to help combat overfitting.
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The results shown in the table below are for automatic speech recognition on the popular TIMIT data set.
Star Trek: Deep Space Nine | Deep Purple | Deep Throat | Deep South | Deep Forest | Deep Springs College | Deep Throat (film) | Cathedral of Learning | Social learning theory | Polish Academy of Learning | Deep One | Run Silent, Run Deep | Learning disability | Deep Throat (The X-Files) | Deep foundation | Waist Deep | Kinesthetic learning | Goldstone Deep Space Communications Complex | deep sea | Deep Elm Records | Clough Undergraduate Learning Commons | Cengage Learning | Visual learning | The Learning Tree | The Deep | Skin Deep | Roll Deep | Renaissance Learning | observational learning | Lords of the Deep |