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Recommender Systems

1012 directly classified papers

Papers per year

Papers

Learning to Recommend from Sparse Data via Generative User Feedback AAAI 2021
RevMan: Revenue-aware Multi-task Online Insurance Recommendation AAAI 2021
Reinforcement Learning with a Disentangled Universal Value Function for Item Recommendation AAAI 2021
Knowledge-aware Coupled Graph Neural Network for Social Recommendation AAAI 2021
Discovering Collaborative Signals for Next POI Recommendation with Iterative Seq2Graph Augmentation IJCAI 2021
Pattern-enhanced Contrastive Policy Learning Network for Sequential Recommendation IJCAI 2021
Contextual Recommendations and Low-Regret Cutting-Plane Algorithms NIPS 2021
Two-sided fairness in rankings via Lorenz dominance NIPS 2021
A/B Testing for Recommender Systems in a Two-sided Marketplace NIPS 2021
Rebounding Bandits for Modeling Satiation Effects NIPS 2021
On Component Interactions in Two-Stage Recommender Systems NIPS 2021
DA-GCN: A Domain-aware Attentive Graph Convolution Network for Shared-account Cross-domain Sequential Recommendation IJCAI 2021
Quantifying Availability and Discovery in Recommender Systems via Stochastic Reachability ICML 2021
Correcting Exposure Bias for Link Recommendation ICML 2021
Improving Sequential Recommendation Consistency with Self-Supervised Imitation IJCAI 2021
Recent Advances in Heterogeneous Relation Learning for Recommendation IJCAI 2021
A Gang of Adversarial Bandits NIPS 2021
PREMERE: Meta-Reweighting via Self-Ensembling for Point-of-Interest Recommendation AAAI 2021
Personalized Outfit Recommendation With Learnable Anchors CVPR 2021
A User-Adaptive Layer Selection Framework for Very Deep Sequential Recommender Models AAAI 2021
Efficient Optimal Selection for Composited Advertising Creatives with Tree Structure AAAI 2021
DEAR: Deep Reinforcement Learning for Online Advertising Impression in Recommender Systems AAAI 2021
Asynchronous Stochastic Gradient Descent for Extreme-Scale Recommender Systems AAAI 2021
Dynamic Tensor Recommender Systems JMLR 2021
Towards Open-World Recommendation: An Inductive Model-based Collaborative Filtering Approach ICML 2021