1Cademy - Classification via an Encoder Function ($Classify_{\omega}(Encode

Learn Before

Uncluttered Notation for Encoder-Classifier Models

Formula

Classification via an Encoder Function ( $Classify_{\omega}(Encode_{\hat{\theta}}(\cdot))$ )

This formula represents a two-stage classification model. First, an input, denoted by the dot ( $\cdot$ ), is processed by an encoder function, $Encode_{\hat{\theta}}$ , which is parameterized by $\hat{\theta}$ . This encoder transforms the input into a new representation. Second, this representation is then passed to a classifier function, $Classify_{\omega}$ , which is parameterized by $\omega$ , to produce the final classification output.