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Questions tagged [batch-learning]

For questions about machine learning algorithms that learn in batches of data rather than one example at a time (i.e. online learning). Batch learning can also be called offline learning and it is the common way of training machine learning models.

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Methodologies for passing the best samples for a neural network to learn

Just an idea I am sure I read in a book some time ago, but I can't remember the name. Given a very large dataset and a neural network (or anything that can learn via something like stochastic gradient ...
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1answer
38 views

Is it okay to calculate the validation loss over batches instead of the whole validation set for speed purposes?

I have about 2000 items in my validation set, would it be reasonable to calculate the loss/error after each epoch on just a subset instead of the whole set, if calculating the whole dataset is very ...
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1answer
125 views

Offline/Batch Reinforcement Learning: when to stop training and what agent to select

Context: My team and I are working on a RL problem for a specific application. We have data collected from user interactions (states, actions, rewards, etc.). It is too costly for us to emulate agents....
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367 views

Why would a VAE train much better with batch sizes closer to 1 over batch size of 100+?

I've been training a VAE to reconstruct human names and when I train it on a batch size of 100+ after about 5 hours of training it tends to just output the same thing regardless of the input and I'm ...
2
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1answer
73 views

Is batch learning with gradient descent equivalent to "rehearsal" in incremental learning?

I am learning about incremental learning and read that rehearsal learning is retraining with old data. In essence, isn't this the exact same thing as batch learning (with stochastic gradient descent)? ...
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1answer
122 views

Why does the output shape of a Dense layer contain a batch size?

I understand that the batch size is the number of examples you pass into the neural network (NN). If the batch size is 10, it means you feed the NN 10 examples at once. Assuming I have an NN with a ...
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1answer
167 views

What is the difference between batches in deep Q learning and supervised learning?

How is the batch loss calculated in both DQNs and simple classifiers? From what I understood, in a classifier, a common method is that you sample a mini-batch, calculate the loss for every example, ...
7
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1answer
3k views

What is the relation between online (or offline) learning and on-policy (or off-policy) algorithms?

In the context of RL, there is the notion of on-policy and off-policy algorithms. I understand the difference between on-policy and off-policy algorithms. Moreover, in RL, there's also the notion of ...