Questions tagged [multitask-learning]
The multitask-learning tag has no usage guidance.
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Can a multi-task model work on conditions for each layer?
I am currently working on a multi-task model that needs to handle car detection, damage segmentation and license plate ocr.
my idea was to only run the OCR layer when there is a license plate detected ...
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Enhancing Soil Moisture Predictions Using Multimodal Data Integration in Agriculture
I am exploring an interdisciplinary research area involving multimodal data, focusing on agriculture. My study incorporates both visual and tabular data: crop and soil images from three distinct ...
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Tile color, shape, and type detection altogether
I'm trying to apply some detections/classification on the set of tiles we have. Specifically, I need to detect color (15 classes), pattern (25 classes- on the surface of tiles, there can be certain ...
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How to force my model heads to learn different things?
I have an Seq2Seq model that has 2 generative LM heads. I want the two heads to focus on different features/styles while decoding. The approach that I was thinking of is adding a distance cost to the ...
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How to compute sample weight in multi-task model?
What's the correct way to calculate sample weight in a multi-task model?
Concretely, I have a model that outputs a 400 class [multi-class] classification, as well as a 5 class multi-label ...
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Is it possible to modify YOLOv8 to use it as a feature extractor for other tasks?
I'm reading through the documentation of YOLOv8 here, but I fail to see an easy way to do what I suggest in the title. What I want to do is to load a pretrained YOLOv8 model, create a bigger model ...
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Large change in validation loss, small change in training loss
I'm training a multi-task, multi-label neural network. I am attempting to tune the architecture and am having some trouble interpreting the learning curves. Particularly, when I look at the learning ...
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Each multi-class output has another level of multi-class output
I want to predict a major class and then minor class.
Major class is a multi-class model which has 4 categories. Each of this categories has 10-15 subcategories, for which I can build a multi-task ...
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Are more target labels in a multi-label classification always better?
Context
We work on medical image segmentation. There are a lot of potential labels for one and the same region we segment. There can be different medically defined labels like anatomical regions, more ...
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Multi-task learning for improving segmentation
I am building a multi-task model, where my main task is segmentation and my auxiliary task is either denoising or image inpainting. The goal is to try to improve the quality of the segmentation with ...
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Multi-modal neural network [closed]
How do you start with creating a multi-modal neural network?
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What is the difference between Multi task learning and domain generalization
I was wondering about the differences between "multi-task learning" and "domain generalization". It seems to me that both of them are types of inductive transfer learning but I'm ...
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How do we bring Pareto optimality into the realm of Machine Learning?
I have a multi-objective optimisation problem with a large number of objectives (more than 10) which is generally the case in most-real life problems. The use of traditional GAs such as NSGA-II or ...
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Emotion Recognition with Multi-task Learning [closed]
Introduction
I am a beginner in Data Science and currently working on a learning project aimed at emotion recognition from a bio-medical sensor dataset.
The dataset consists of 8 sensors data from 20 ...
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Tips for improving multitask learning based on multiple outputs
I'm currently trying to use multi-task learning based on a multi-output model that both allows to get an output for classification and regression. However, at the moment it's staying at around 20% ...
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What kind of learning problem is this?
Say I have $n$ multi-class classification problems $p_1$, ..., $p_n$. Each of these have their own training data. While they are all distinct problems, there may be similarities in their data (which ...
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Which is better: multi-output model or separate models for similar tasks?
I am working on two problems:
classification of images into high-level classes (e.g. shoe, dress, jacket etc.)
classification of the attributes of the same images on a lower level (e.g. shoe style, ...
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Multitask learning model with variable number of tasks
This is my basic multitask learning model, and it has 2 tasks. Since there are only 2 tasks, maybe I can duplicate the code for each task as self.tower1 and self.tower2.
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ImageDataGenerator for multi task output in Keras using flow_from_directory
I am creating a multitask CNN model and I have two different classification properties (one with 10 classes, 2nd with 5 classes) and my directory structure looks like this:
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How to feed data to multi-output Keras model from a single TFRecords file
I know how to feed data to a multi-output Keras model using numpy arrays for the training data. However, I have all my data in a single TFRecords file comprising several feature columns: an image, ...
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Combining heterogeneous data sets for more powerful machine learning
Suppose we have two data sets of movie reviews; one from IMDB and one from Rotten Tomatoes (RT). Each entry has a written-review and a score attached to it. The concatenated datasets might look like
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Implementing Multitask Classification in Keras
I am Trying to implement Multitask Learning in Keras with share constitutional Layers and task specific FC layers.
Following is my model:
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Architecture for multivariate multi-time-series model where some features are TS specific and some features are global
I'm looking to build a time series model (using a TCN or a LSTM) with $N$ different series, each of which has $P$ series-specific features $\mathbf{X}$. My input array is of dimension $N \times t \...
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Why and how BERT can learn different attentions for each head?
https://towardsdatascience.com/deconstructing-bert-distilling-6-patterns-from-100-million-parameters-b49113672f77
I read the blog above. It visualizes that different color/head has different ...
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Should I rescale losses before combining them for multitask learning?
I have a multitask network taking one input and trying to achieve two tasks (with several shared layers, and then separate layers).
One task is multiclass classification using the CrossEntropy loss, ...
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Missing outputs in multiple-output neural net
I am looking at a task, where I want to predict multiple things from an image (an animal's breed [categorical], age [continuous number] and gender [categorical]). Unsurprisingly, my first thought was ...
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Thoughts on improving the Multitask Learning Model
Any Thoughts on improving the Model. So far i was able to achieve around accuracy 0.20 on each task specific dense network of a Multi task Learning Architecture. I have posted model and validation ...
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Multi task learning architecture for Multi-label classification
I am working a classification problem. The dataset was collected from Painters by number, a competition hosted by kaggle. The task is to identify painter,style and genre given paintings.
So far, I ...
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Multi target classification for different types of target variables
I am new to machine learning and I got this task in my university. I have a dataset with over 100 columns and two target variables: $target1$ is categorical i.e. $0$ or $1$ and $target2$ is continuous ...
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Multi task learning in Keras
I am trying to implement shared layers in Keras. I do see that Keras has keras.layers.concatenate, but I am unsure from documentation about its use. Can I use it to ...
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Multitask learning NN only trains on a few tasks
I am fairly new to the Machine Learning field, but I am working on building a multi-task network for a project I am working on. Unfortunately, despite all my best googling and digging through ...
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Multi-task learning for Multi-label classification?
I have a multi-label classification problem wherein each example can belong to one of the pre-defined classes (or can belong to none of them).
I was wondering if I can somehow apply multi-task ...
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Multi-Source Time Series Data Prediction
I was wondering if anyone has experience with time series prediction for data from multiple sources. So for instance, time series $a,b,..,z$ each have their own shape, some may be correlated with ...
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Error on multitask neural nets where all outputs not observed for every example
Let's say I have 2 datasets, each from a set of experiments. Dataset A measures a set of properties X for set S, while dataset B measures properties Y for set T. X and Y are highly correlated, and S ...
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How to do multitask learning using Caffe?
I wonder how to do multitask learning using Caffe. Should I simply use the output layer SigmoidCrossEntropyLoss or EuclideanLoss, and define more than one outputs?
E.g. is the following architecture ...
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