# Tag Info

Accepted

### How can I estimate how many photos I need to train ResNet-50 for image classification?

What you want to calculate/estimate is known as the sample complexity in computational learning theory. If you knew the VC dimension of the neural network, you may be able to estimate the sample ...
• 41k
Accepted

### Do the terms 'sample complexity' and 'sample efficiency' mean the same thing in RL context

The sample complexity is defined precisely in computational learning theory, which studies learning from a theoretical standpoint (like theoretical physics for physics). Here's a definition taken from ...
• 41k
Accepted

### Is there a way to define the boundaries of the optimal size of a training set?

For a finite value to be 'optimal,' typically you need some benefit from more paired up with some cost for more, and eventually the lines cross because the benefit decreases and the cost increases. ...
• 4,272

### How does size of the dataset depend on VC dimension of the hypothesis class?

Given a hypothesis set $H$, the set of all possible mappings from $X\to Y$ where $X$ is our input space and $Y$ are our binary mappings: $\{-1,1\}$, the growth function, $\Pi_H(m)$, is defined as the ...
Accepted

### How does size of the dataset depend on VC dimension of the hypothesis class?

From [1] we know that we have the following bound between the test and train error for i.i.d samples:  \mathbb{P}\left(R \leqslant R_{emp} + \sqrt{\frac{d\left(\log{\left(\frac{2m}{d}\right)}+1\...
• 1,826

### How does size of the dataset depend on VC dimension of the hypothesis class?

The VC dimension represents the capacity (the same Vapnik, the letter V from VC, calls it the "capacity") of a model (or, in general, hypotheses class), so a model with a higher VC dimension has more ...
• 41k
Accepted

### No-Free-Lunch: Calculation of the number of sequences of examples of size $m$

Your expression is "how many ways can I choose m unique elements from a list of 2m unique elements" The author's expression is "how many unique sequences of length m can I construct ...
• 32.8k
1 vote
Accepted

### Is there a measure of model complexity?

Yes. There are at least 2 measures of model complexity studied and used in learning theory: VC dimension and Rademacher complexity. If you're new to learning theory, you could take a look at this ...
• 41k
1 vote

### Is there any practical application of knowing whether a concept class is PAC-learnable?

Is there any practical application of knowing whether a concept class is PAC-learnable? If you know that a concept class is PAC-learnable (i.e. its VC dimension is finite), then there's a possibility ...
• 41k
1 vote

### How many training data is required for GAN?

There is no one answer to this. In general, the bigger your model is, the more data you will need to train it. You tak about training a classifier. In this case it also depends on the difficulty (or ...
• 226
1 vote

### Is there a way to define the boundaries of the optimal size of a training set?

In general, the larger the training set, the better. See The Unreasonable effectiveness of Data, though this article is quite dated (written in 2009). Xavier Amatriain, a researcher at Netflix has a ...
• 1,325

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