Questions tagged [domain-adaptation]

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Understanding the implementation of domain adaptation algorithm

I'm trying to implement domain adaptation using stochastic neighborhood embedding based on this article. I have different input shapes in target and source domain and using 2 parallel CNNs for ...
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0answers
14 views

Train on multi-domains, then fine-tune on specific domain

Would it make sense to first train a model on images from multiple domains, and then do "fine-tuning" on one specific domain to improve its performance on it? For instance, one could train an object ...
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1answer
142 views

How to measure the performance of a domain adaptation /Transfer learning technique? [closed]

Given that the performance you achieve depends on how far the target from the source domain is, how can you judge the performance of an algorithm?
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0answers
18 views

Domain adaption vs. heirarchical model - when to use which?

I know a little bit about domain adaption and also about random effects models, but I'm a little unsure if they're at all compatible. Domain adaptive models (based on ANNs) usually try to find some ...
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1answer
79 views

Why does increasing the training set size not improve the results?

I have trained a model on a training set, which is not that big (overall around 120 true positives, and of course lots of negative examples). What I am trying to do is to improve the results by ...
3
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1answer
1k views

What is the difference between BatchNorm and Adaptive BatchNorm (AdaBN)?

I understand that BatchNorm (Batch Normalization) centers to (mean, std) = (0, 1) and potentially scales (with $ \gamma $) and offsets (with $ \beta $) the data which is input to the layer. BatchNorm ...
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4answers
475 views

Discrepancy between training set and real-world data set: domain adaptation?

I have read in literature that in some cases the training set is not representative for a real-world dataset. However, I cannot seem to find a proper term describing this phenomenon; what is the ...
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2answers
672 views

Training data from different sources

I am working on a binary classification problem. My data contains 100K samples from two different sources. When I perform the training and testing on data from the first source I can achieve ...
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2answers
377 views

Dealing with an apparently inseparable dataset

I'm attempting to build a model/suite of models to predict a binary target. The exact details of the models aren't important, but suffice to say that I've tried with half a dozen different types of ...