Learning Disentangled User Representation Based on Controllable VAE for Recommendation

Mathematics

• Collaborative Filtering 100%
• Recommendations 94%
• Learning 80%
• Trade-offs 60%
• Recommender Systems 48%
• Purchasing 44%
• Interpretability 38%
• Hyperparameters 36%
• Kullback-Leibler Divergence 36%
• Balancing 33%
• Baseline 32%
• Experimental Results 29%
• Directly proportional 25%
• Gaussian distribution 24%
• Robustness 24%
• Evaluate 23%
• Output 21%
• Interaction 21%
• Model 19%
• Derivative 18%
• Concepts 15%

Engineering & Materials Science

• Collaborative filtering 99%
• Purchasing 50%
• Gaussian distribution 49%
• Recommender systems 44%
• Derivatives 36%
• Feedback 27%