Artificial Intelligence Stack Exchange
Artificial Intelligence Stack Exchange

Questions tagged [incremental-learning]

For questions related to incremental learning algorithms, which are algorithms that attempt to learn new information without forgetting all the previously learned one. Incremental learning is often a synonym for continual (or continuous) learning and lifelong learning.

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Are neural networks prone to catastrophic forgetting?

Imagine you show a neural network a picture of a lion 100 times and label it with "dangerous", so it learns that lions are dangerous. Now imagine that previously you have shown it millions of images of lions and alternatively labeled it as…
zooby
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Is it possible to train a neural network as new classes are given?

I would like to train a neural network (NN) where the output classes are not (all) defined from the start. More and more classes will be introduced later based on incoming data. This means that, every time I introduce a new class, I would need to…
Fr_nkenstien
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What do you call a machine learning system that keeps on learning?

As I understand it from this video lecture, there are three types of deep learning: Supervised Unsupervised Reinforcement All these can serve to train a neural network either only prior to its deployment or during its operating. For the latter…
ZakC
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Are there dynamic neural networks?

Are there neural networks that can decide to add/delete neurons (or change the neuron models/activation functions or change the assigned meaning for neurons), links or even complete layers during execution time? I guess that such neural networks…
TomR
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What is the difference between learning without forgetting and transfer learning?

I would like to incrementally train my model with my current dataset and I asked this question on Github, which is what I'm using SSD MobileNet v1. Someone there told me about learning without forgetting. I'm now confused between learning without…
abhimanyuaryan
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What are the state-of-the-art approaches for continual learning with neural networks?

There seems to be a lot of literature and research on the problems of stochastic gradient descent and catastrophic forgetting, but I can't find much on solutions to perform continual learning with neural network architectures. By continual learning,…
gcorso
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Can I train a neural network incrementally given new daily data?

I would like to know if it was possible to train a neural network on daily new data. Let me explain this more in detail. Let's say you have daily data from 2010 to 2019. You train your NN on all of it, but, from now on, every day in 2019 you get new…
neomatriciel
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Is continuous learning possible with a deep convolutional neural network, without changing its topology?

In general, is continuous learning possible with a deep convolutional neural network, without changing its topology? In my case, I want to use a convolutional neural network as a classifier of heartbeat types. The ECG signal is split, and a color…
Dominiksr
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Can a CNN be trained incrementally?

Like our human brain, we can first learn (train) the handwriting 0 and 1. After the traing (and test) accuray is good enough, we only need to study (traing) the hardwriting 2, Instead of cleaning all of learned memory, and relearn handwriting data…
Sunson29
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What are stable ways of doing online machine learning?

I am trying to deploy a machine learning solution online into an application for a client. One thing they requested is that the solution must be able to learn online because the problem may be non-stationary and they want the solution to track the…
Rui Nian
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What is the name of an AI system that learns by trial and error?

Imagine a system that controls dampers in a complex vent system that has an objective to perfectly equalize the output from each vent. The system has sensors for damper position, flow at various locations and at each vent. The system is initially…
SchroedingersCat
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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…
JobHunter69
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Transfer learning to train only for a new class while not affecting the predictions of the other class

I am basically interested in vehicle on the road. YoloV3 pytorch is giving a decent result. So my interested Vehicles Car Motorbike Bicycle Truck and bus, I have a small vehicles being detected as truck. Since the small vehicle is nicely being…
Santhosh Dhaipule Chandrakanth
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How can I incrementally train a Yolo model without catastrophic forgetting?

I have successfully trained a Yolo model to recognize k classes. Now I want to train by adding k+1 class to the pre-trained weights (k classes) without forgetting previous k classes. Ideally, I want to keep adding classes and train over the previous…
Troy
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Will training an AI still work if the input data is somewhat sparse?

I'm looking at writing an AI agent for pattern recognition. I want to be able to constantly feed new data to the AI to continuously train it as new data may have new patterns. My problem, though, is that my input feed may break once in a while (the…
Alexis Wilke
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