Contents
🚗 2. adversarial training (adversarial perturbations)
🚗 3. adversarial learning (generative adversarial network)
- paper notes on APOIR
- paper notes on Cascading DQN
- paper notes on DASO
- paper notes on ESRF
- paper notes on Geo-ALM
- paper notes on LARA
- paper notes on MFGAN
- Title:Adversarial Personalized Ranking for Recommendation[🌟first train MF with BPR, and then further optimize it under APR framework]
- Title: Adversarial Learning to Compare: Self-Attentive Prospective Customer Recommendation in Location based Social Networks[🌟prospective customer recommendation, recommend by making comparisons among users’ historical check-ins with adversarial training]
- Title: Adversarial Point-of-Interest Recommendation[🌟geographical and social influence are also incorporated]
- Title: Generative Adversarial User Model for Reinforcement Learning Based Recommendation System[🌟Using the estimated user behavior model φ and the corresponding reward function r as the simulation environment, then use reinforcement learning to obtain a recommendation policy.]
- Title: Deep Adversarial Social Recommendation[🌟bidirectional mappings between the user-item interactions (item domain) and user-user connections (social domain)]
- Title: Enhancing Social Recommendation with Adversarial Graph Convolutional Networks[🌟alternative neighborhood generation, neighborhood denoising, and attention-aware social recommendation, GCN based]
- Title: Geo-ALM: POI Recommendation by Fusing Geographical Information and Adversarial Learning Mechanism[🌟fuse geographical features with generative adversarial networks(GAN)]
- Title: LARA: Attribute-to-feature Adversarial Learning for New-item Recommendation[🌟aim to optimize a matching problem between existing users and a virtual user profile generated from attributes of the targeting new-item(item cold-start problem)]
- Title: Sequential Recommendation with Self-AttentiveMulti-Adversarial Network[🌟a Transformer-based generator taking user behavior sequences as input to recommend the possible next items, multiple factor-specific discriminators to evaluate the generated sub-sequence from the perspectives of different factors]