Summary of On-device Federated Learning in Smartphones For Detecting Depression From Reddit Posts, by Mustofa Ahmed et al.
On-device Federated Learning in Smartphones for Detecting Depression from Reddit Posts
by Mustofa Ahmed, Abdul Muntakim, Nawrin Tabassum, Mohammad Asifur Rahim, Faisal Muhammad Shah
First submitted to arxiv on: 17 Oct 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: None
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper explores depression detection using deep learning models, leveraging social media data to identify patterns in mental health conditions. It focuses on Federated Learning (FL) as a decentralized approach to train models on smartphones while protecting user privacy. The authors train three neural network architectures (GRU, RNN, and LSTM) on Reddit posts to detect signs of depression, evaluating performance under heterogeneous FL settings. To optimize the training process, they use a common tokenizer across client devices, reducing computational load. Additionally, they analyze resource consumption and communication costs in a real-world FL environment. The results demonstrate that federated models achieve comparable performance to centralized models. This study highlights the potential of FL for decentralized mental health prediction by providing a secure and efficient model training process on edge devices. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper looks at using computers to help detect depression from social media posts. It wants to find a way to do this without storing personal information, so it uses a special kind of computer learning called Federated Learning (FL). The researchers train three different types of neural networks (GRU, RNN, and LSTM) on Reddit posts to recognize signs of depression. They test how well these models work when they’re trained separately on each phone, which helps keep personal information private. The results show that the computer models can be just as good at detecting depression as more powerful computers. This is important because it could help people get help for their mental health without sharing too much about themselves. |
Keywords
» Artificial intelligence » Deep learning » Federated learning » Lstm » Neural network » Rnn » Tokenizer
