#embedding-learning News & Analysis

2 articles tagged with #embedding-learning. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

2 articles

AINeutralarXiv – CS AI · Jun 95/10

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A Universal Dense Football Event Representation Based on TabTransformer

Researchers propose a TabTransformer-based neural network that learns dense representations of football event data by treating categorical features as learned embeddings rather than one-hot encodings. The approach captures sport-specific action semantics during pretraining, enabling superior performance on downstream tasks like action value estimation and play style recognition.

AINeutralarXiv – CS AI · Jun 56/10

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Bridging the Semantic-Collaborative Gap: An Asymmetric Graph Architecture for Cold-Start Item Recommendation

Researchers at Tubi have developed Shallow-RHS, a graph-based recommendation system that addresses the cold-start problem for new content by using asymmetric neural architectures. The model separates user-interaction modeling from content feature encoding, enabling immediate embeddings for newly ingested items while maintaining collaborative filtering capabilities in production environments.