How to formulate a loss function that minimizes both cross-entropy and an additional term?

Research & Models
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#1

How to formulate a loss function that minimizes both cross-entropy and an additional term ?

#3

Hi @MrAb2 ,

To formulate a loss function that minimizes both cross-entropy and an additional term, you can combine the two terms by assigning weights to each term and adding them together. The weight determines the relative importance given to each term in the overall loss function.

Loss function = w1 * cross-entropy + w2 * additional term

Adjusting these weights allows you to control the impact of each term on the overall loss, and you can optimize the loss function using gradient-based optimization algorithms such as SGD, Adam, Adagrad, etc. to find the optimal model parameters that minimize the combined loss.

I hope this helps!

Thanks.

1 Like
#5

Hi @Laxma_Reddy_Patlolla ,

Thank you for your suggestion. I appreciate your input. Could you please provide me with more information or references to support your proposed solution? I want to make sure I have a solid understanding and theoretical proof before implementing it.

Thanks

#6

Hi @MrAb2 ,

Could you please look into this article for more information.I have referred to various documents based on those that answered your question. After going through this article, if you find any more helpful information than I mentioned, please share it with us.

I hope this helps!

Thanks.

1 Like
#8

Hi @Laxma_Reddy_Patlolla ,
That’s exactly what I was looking for.
Thanks,