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## Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks (MAML)
- Authors: Chelsea Finn, Pieter Abbeel, Sergey Levine
- Organization: UC Berkeley & OpenAI
- Conference: ICML 2017
- Pap…
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### Background Research
The lists below are the most heavily cited recent survey papers that may be relevant to our project. After the meta-review has been conducted, identify newer techniques that r…
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### System Info
Hi there, I met a bug that when using TGI Gaudi 2.0.5 with both meta-llama/Meta-Llama-3-8B-Instruct and Intel/neural-chat-7b-v3-3. When I set the default frequency/repetition/presen…
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# Rational:
Machine learning models usually apply meta-parameter optimization to find the learning parameters that lead to the better learning and better cross-validation. So to here, to get a bio…
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E. Triantafillou et. al. [1] had experiments for few-shot learning with class imbalance to see if the class imbalance actually impacts to the performance of the few-shot learning methods.
**Resul…
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Implement the best practices from multi-agent Rl community and stablebaselines3 into our algorithm. Further analyse similarities between petting zoo multi-agent implementation to current RL implementa…
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# Reference
- [ ] [paper - 2007 - An overview of bilevel optimization](http://www.iro.umontreal.ca/~marcotte/ARTIPS/AOR2007.pdf)
- [ ] [paper - 2020 - Meta-Learning in Neural Networks: A Survey - 2.…
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- [ ] [Connecting cortex to machines: recent advances in brain interfaces](https://www.nature.com/articles/nn947) (2002)
- [ ] [Visual P300 Mind-Speller Brain-Computer Interfaces: A Walk Through t…
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Hi! I've recently been hyperparameter tuning for the OCMAML algorithm on the MNIST dataset and I ran into this error when trying to use the dense_layers argument:
> Traceback (most recent call last…
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# Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Meta-learningとは、学習方法を学習するアルゴリズムの一種。「**少しのデータ・学習ステップの後、すぐに新しいタスクに適応できるモデル**」を学習するこを目標としている。本論文で提案しているModel-Agnostic Meta-Learning …