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Found 5 papers, 3 papers with code
Context-Aware Sequential Model for Multi-Behaviour Recommendation
Sequential recommendation models are crucial for next-item recommendations in online platforms, capturing complex patterns in user interactions.
CARCA: Context and Attribute-Aware Next-Item Recommendation via Cross-Attention
This cross-attention allows CARCA to harness the correlation between old and recent items in the user profile and their influence on deciding which item to recommend next.
Ranked #1 on
Sequential Recommendation
on Amazon Men
(using extra training data)
A.I. and Data-Driven Mobility at Volkswagen Financial Services AG
Machine learning is being widely adapted in industrial applications owing to the capabilities of commercially available hardware and rapidly advancing research.
Do We Really Need Deep Learning Models for Time Series Forecasting?
In this paper, we report the results of prominent deep learning models with respect to a well-known machine learning baseline, a Gradient Boosting Regression Tree (GBRT) model.
Multi-Label Network Classification via Weighted Personalized Factorizations
It can be formalized as a multi-relational learning task for predicting nodes labels based on their relations within the network.
