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2 votes

Would maximizing (instead of minimizing) error of an LLM/HMM lead to complex behavior?

You cannot really invert the loss, because that's undefined most likely. Take linear regression with OLS, then we know that the loss function is quadratic wrt the parameters (assuming to have 1 ...
Alberto's user avatar
  • 2,153
2 votes
Accepted

What are the differences between loss surfaces that "derive"from different observations?

Let's take in consideration linear regression. You have a dataset composed by $x,y$ pairs, and you assume they are linearly related, thus you model this problem with LR: $$ y = wx+b $$ Now, you want ...
Alberto's user avatar
  • 2,153
2 votes

What role does data quality plays in the LLM scaling laws?

is the set of values estimated by the Chinchilla scaling laws optimal for these smaller models with optimized data too? This is an open research question, but some research such as Beyond neural ...
Stella Biderman's user avatar
1 vote
Accepted

Can I scale subsets of my dataset independently to handle different feature ranges?

Scaling individual parts of a dataset individually is generally not that trivial. Just remember that this means that the statistical properties of the subsets also may change. E.g., let's assume that ...
BanDoP's user avatar
  • 193
1 vote

How do I know that my dataset is good enough for training a neural network?

You can't really know for sure, unless you know all possible values that can be sampled from the distribution or know the distribution - in that case, you don't need machine learning and you can just ...
nbro's user avatar
  • 40.8k
1 vote
Accepted

Do different camera angles affect the performance of the deep learning model?

Yes, changing camera height can affect the performance of models in applications like face recognition. Because it will change the face-capturing angle and size of the face captured. But do not worry, ...
Hiren Namera's user avatar
1 vote

Would maximizing (instead of minimizing) error of an LLM/HMM lead to complex behavior?

In HMM, a simple mechanism to reduce overfitting and therefore generating variety in the system output is tweaking the transition matrix A and/or the symbol emission probability B. Allowing for some ...
Jaume Oliver Lafont's user avatar
1 vote

How to perform binary classification when one class is more predominant than the other?

From your case, it seems like you want your algorithm to classify both 1s and 0s with high accuracy. To increase the number of 1s and get it to a comparable level as 0s, you could generate new ...
AdiCoder's user avatar

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