Questions tagged [meta-learning]

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How to use efficient net as feature extractor for meta/Few shot learning in PyTorch

I am working on few shot learning and I wanted to use efficient-net as backbone feature extractor. Most of the model use Resnet as feature extractor. For example I can use below line of code and it ...
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26 views

Is this a task of meta-learning or transfer learning?

I have a task that I am not able to identify if it is of transfer or meta learning. I want to know this, in order to ask help in solving it, because there are some parts that I have not understood. ...
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9 views

How to make Training Data for Meta-Learning

If I am doing 5-way-1-shot meta learning on dataset with 200 classes, what would be the sample space for my labels? I know there would be 5 labels in each meta-set, but will I be chosing labels from ...
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21 views

Difference between neural architecture search (NAS) and Meta Learning

Is NAS a separate domain when compared to Meta Learning or does it fall under Meta learning? To be more precise. Is 1 or 2 correct? Or is it something completely different?
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42 views

Siamese vs matching network for correct image category matching

I have to find the closest match between my image and bunch of already collected images of different classes in the folder. Whic meta-learning approach should I select. I am thinking about the Siamese ...
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17 views

Reconciling a vector input with a scalar operation?

I've been studying the topic of Meta-Learning. I am particularly interested in Regularized Evolution. I have been trying to replicate the work presented here: https://ai.googleblog.com/2020/07/automl-...
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88 views

Stacking - Appropriate base and meta models

When implementing stacking for model building and prediction (For example using sklearn's StackingRegressor function) what is the appropriate choice of models for the base models and final meta model?...
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1answer
96 views

How to implement my own loss function for Prototype learning using Keras Model

I'm trying to migrate this code, "Omniglot Character Set Classification Using Prototypical Network", into Tensorflow 2.1.0 and Keras 2.3.1. My problem is about how to use euclidean distance between ...
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57 views

Meta Learning: how to train a model with Support Set and Query Set

I've just started to learn Meta Learning reading the book Hands-On Meta Learning with Python. I think I know the answer for my question, but I'm a little confuse about how to implement the algorithm ...
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1answer
183 views

How to optimize hyperparameters in stacked model?

I was wondering whether somebody could explain how to optimize hyperparameters for the base learners and meta algorithm when stacking? In many tutorials they seem to be plucked out of thin air! ...
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1answer
910 views

Automatically uses several cores on R

I am using a library called MFE to generate meta-features. However, I am working right now with several files and I notice that I am using only 1 core of my machine and taking too much time. I have ...
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46 views

Are there any Meta Knowledge bank available?

What resources do you use to learn meta knowledge ? By meta knowledge, I mean generalized information that will help us take more informed decisions when working on a problem later. Example of meta ...
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1answer
681 views

How to search for an optimal dithering pattern?

I'm trying to find an optimal dithering pattern which can be used as a threshold on a greyscale image to generate a 1 bit black and white image. Ideally it would be optimal in the sense that a human ...
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131 views

How to feed the input to a Memory Augmented Neural Network (MAAN) to do one shot learning?

In this paper by Deep-Mind on one shot learning they have published an architecture explaining how the system works with an external meory. I understand the mechanism perfectly. But what I don't ...
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48 views

Isn't the optimizer network in deepminds learning to learn a DRQN?

In the paper "Learning to learn by gradient descent by gradient descent" they describe an RNN which learns gradient transformation to learn an optimizer. The optimizer network directly interacts ...
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1answer
83 views

Can clustering my data first help me learn better classifiers?

I was thinking about this lately. Let's say that we have a very complex space, which makes it hard to learn a classifier that can efficiently split it. But what if this very complex space is actually ...