Skip to main content
Artificial Intelligence

Return to Question

Bumped by Community user
Bumped by Community user
Bumped by Community user
Bumped by Community user
Bumped by Community user
Bumped by Community user
Bumped by Community user
Bumped by Community user
Bumped by Community user
Bumped by Community user
Bumped by Community user
Bumped by Community user
Bumped by Community user
edited tags
Source Link
nbro
nbro
  • 41.4k
  • 12
  • 114
  • 205

Is regular/offlinebatch learning with gradient descent ANN training equivalent to "rehearsal" in incremental learning?

I am self-learning incremental learning about incremental learning and read that rehearsalrehearsal learning is retraining with old data. In essence, isn't this the exact same thing as normal batch/stochastic learning (with stochastic gradient descent)? You train a model by passing in batches of data and redo this with a set number of epochs.

If I'm understanding rehearsal learning correctly, you do the exact same thing but with "new" data. Thus, the only difference is inconsistencies in the epoch number across data batches.

Is regular/offline gradient descent ANN training equivalent to "rehearsal" in incremental learning?

I am self-learning incremental learning and read that rehearsal learning is retraining with old data. In essence, isn't this the exact same thing as normal batch/stochastic gradient descent? You train a model by passing in batches of data and redo this with a set number of epochs.

If I'm understanding rehearsal learning correctly, you do the exact same thing but with "new" data. Thus, the only difference is inconsistencies in the epoch number across data batches.

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)? You train a model by passing in batches of data and redo this with a set number of epochs.

If I'm understanding rehearsal learning correctly, you do the exact same thing but with "new" data. Thus, the only difference is inconsistencies in the epoch number across data batches.

deleted 1 character in body
Source Link
JobHunter69
JobHunter69
  • 233
  • 1
  • 10

I am self-learning incremental learning and read that rehearsal learning is retraining with old data. In essence, isn't this the exact same thing as normal batch/stochastic gradient descent? You train a model by passing in batches of data and redo this with a set number of epochs.

If I'm understanding rehearsal learning correctly, you do the exact same thing but with "new" data so that. Thus, the only difference is inconsistencies in the epoch number across data batches.

I am self-learning incremental learning and read that rehearsal learning is retraining with old data. In essence, isn't this the exact same thing as normal batch/stochastic gradient descent? You train a model by passing in batches of data and redo this with a set number of epochs.

If I'm understanding rehearsal learning correctly, you do the exact same thing but with "new" data so that the only difference is inconsistencies in the epoch number across data batches.

I am self-learning incremental learning and read that rehearsal learning is retraining with old data. In essence, isn't this the exact same thing as normal batch/stochastic gradient descent? You train a model by passing in batches of data and redo this with a set number of epochs.

If I'm understanding rehearsal learning correctly, you do the exact same thing but with "new" data. Thus, the only difference is inconsistencies in the epoch number across data batches.

Source Link
JobHunter69
JobHunter69
  • 233
  • 1
  • 10

Is regular/offline gradient descent ANN training equivalent to "rehearsal" in incremental learning?

I am self-learning incremental learning and read that rehearsal learning is retraining with old data. In essence, isn't this the exact same thing as normal batch/stochastic gradient descent? You train a model by passing in batches of data and redo this with a set number of epochs.

If I'm understanding rehearsal learning correctly, you do the exact same thing but with "new" data so that the only difference is inconsistencies in the epoch number across data batches.