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Found 5 papers, 0 papers with code
COMET: Convolutional Dimension Interaction for Collaborative Filtering
In this paper, we propose a novel representation learning-based model called COMET (COnvolutional diMEnsion inTeraction), which simultaneously models the high-order interaction patterns among historical interactions and embedding dimensions.
GLIMG: Global and Local Item Graphs for Top-N Recommender Systems
We argue that recommendation on global and local graphs outperforms that on a single global graph or multiple local graphs.
Feature Shapley: A general framework to discovering useful feature interactions
A machine learning system is typically composed of model and data.
Attention over Self-attention:Intention-aware Re-ranking with Dynamic Transformer Encoders for Recommendation
We then introduce a dynamic transformer encoder (DTE) to capture user-specific inter-item relationships among item candidates by seamlessly accommodating the learned latent user intentions via IDM.
Cross-Problem Learning for Solving Vehicle Routing Problems
Accordingly, we propose to pre-train the backbone Transformer for TSP, and then apply it in the process of fine-tuning the Transformer models for each target VRP variant.
