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.

Filter by
Sorted by
Tagged with
0
votes
1answer
33 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 ...
1
vote
0answers
29 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....
1
vote
0answers
96 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
votes
1answer
63 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)? ...
0
votes
1answer
49 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 ...
4
votes
1answer
2k 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 ...