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Found 2 papers, 1 papers with code
Integrating Hyperparameter Search into Model-Free AutoML with Context-Free Grammars
This is very important for the practice of machine learning, as it allows building strong baselines quickly, improving the efficiency of the data scientists, and reducing the time to production.
Constraining Latent Space to Improve Deep Self-Supervised e-Commerce Products Embeddings for Downstream Tasks
Examples of this are models like Prod2Vec or Meta-Prod2Vec which leverage from the information of a user session in order to generate vectors of the products that can be used in product recommendations.
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