Questions tagged [multi-task-learning]
For questions related to multi-task learning (MTL), which is a subfield of machine learning in which multiple learning tasks are solved at the same time, while exploiting commonalities and differences across tasks. MTL can result in improved learning efficiency and prediction accuracy for the task-specific models, when compared to training the models separately.
8 questions with no upvoted or accepted answers
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Multi-objective training involving maximization of one loss function and minimization of another
I need my model to predict $s$ from my data $x$. Additionally, I need the model to not use signals in $x$ that are predictive of a separate target $a$. My approach is to transform $x$ into a ...
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Do the terms multi-task and multi-output refer to the same thing in the context of deep learning?
Do the terms multi-task and multi-output refer to the same thing in the context of deep learning (with neural networks)? For example, do neural networks for multi-task learning use multiple outputs?
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Is optimizing weighted sum multi objective tasks considered a multi-task learning?
I have two sequence prediction tasks, finding $\vec{\pi} \in \Pi$ and $\vec{\psi} \in \Psi$. Each sequence has its own objective function, i.e. $f_1(\vec{\pi})$ and $f_2(\vec{\psi})$. The input for ...
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Multi-task objective sometimes improve single-task performance, but is this true when fine tuning?
It is known that multitask objectives in neural networks sometimes have the effect of improving the performance of the neural network for each of the tasks individually (versus training the same ...
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How do I format task features with a one-hot task identification vector to ensure separate weight matrices for each task in multi-task RL?
I am on Lecture 2 of Stanford CS330 Multi-Task and Meta-learning, and on slide 10, the professor describes using a one-hot input vector to represent the task, and she also explained that there would ...
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Why is my multi-task-learning model not working?
I'm writing Python code to predict fetal head circumference using regression and classification together in a single model.
The model will train to classify a fetal head image into a range (e.g., 50–...
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How to generate original training videos based on existing videoset?
I am a software engineer who is quickly ramping up on AI tech, but am nevertheless very new to the sector.
A collegue has an extensive collection of training videos, the vertical is wheelchair seating ...
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References for the theory of pretraining and unsupervised learning to improve subsequent supervised learning
I am not sure if the title of this post uses the correct terminology, so suggestions are welcome.
I have been following a lot of the ideas of using Pre-training methods on neural networks, to improve ...
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