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add new sections and some todos
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lukas-heilgenbrunner 2024-12-20 12:33:54 +01:00
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@ -210,7 +210,7 @@ CAML (Context aware meta learning) is one of the state-of-the-art methods for fe
Todo Todo
=== Softmax === Softmax
#todo[Maybe remove this section]
The Softmax function @softmax #cite(<liang2017soft>) converts $n$ numbers of a vector into a probability distribution. The Softmax function @softmax #cite(<liang2017soft>) converts $n$ numbers of a vector into a probability distribution.
Its a generalization of the Sigmoid function and often used as an Activation Layer in neural networks. Its a generalization of the Sigmoid function and often used as an Activation Layer in neural networks.
@ -222,6 +222,7 @@ The softmax function has high similarities with the Boltzmann distribution and w
=== Cross Entropy Loss === Cross Entropy Loss
#todo[Maybe remove this section]
Cross Entropy Loss is a well established loss function in machine learning. Cross Entropy Loss is a well established loss function in machine learning.
Equation~\eqref{eq:crelformal}\cite{crossentropy} shows the formal general definition of the Cross Entropy Loss. Equation~\eqref{eq:crelformal}\cite{crossentropy} shows the formal general definition of the Cross Entropy Loss.
And equation~\eqref{eq:crelbinary} is the special case of the general Cross Entropy Loss for binary classification tasks. And equation~\eqref{eq:crelbinary} is the special case of the general Cross Entropy Loss for binary classification tasks.
@ -234,7 +235,9 @@ $
Equation~$cal(L)(p,q)$~\eqref{eq:crelbinarybatch}\cite{handsonaiI} is the Binary Cross Entropy Loss for a batch of size $cal(B)$ and used for model training in this Practical Work. Equation~$cal(L)(p,q)$~\eqref{eq:crelbinarybatch}\cite{handsonaiI} is the Binary Cross Entropy Loss for a batch of size $cal(B)$ and used for model training in this Practical Work.
=== Mathematical modeling of problem === Cosine Similarity
=== Euclidean Distance
== Alternative Methods == Alternative Methods