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20172022
most citedReliable Representations Make A Stronger Defender: Unsupervised Structure Refinement for Robust GNN

66 citations · 142 across the 12 of their papers we have counts for

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6 papers · 1 filter

cs.LG2022★ 66 cited

Reliable Representations Make A Stronger Defender: Unsupervised Structure Refinement for Robust GNN

Kuan Li, Yang Liu, Xiang Ao +4

Benefiting from the message passing mechanism, Graph Neural Networks (GNNs) have been successful on flourish tasks over graph data. However, recent studies have shown that attacker…

cs.LG2021★ 13 cited

Modelling of Bi-directional Spatio-Temporal Dependence and Users' Dynamic Preferences for Missing POI Check-in Identification

Dongbo Xi, Fuzhen Zhuang, Yanchi Liu +3

Human mobility data accumulated from Point-of-Interest (POI) check-ins provides great opportunity for user behavior understanding. However, data quality issues (e.g., geolocation i…

cs.LG2019

Learning beyond Predefined Label Space via Bayesian Nonparametric Topic Modelling

Changying Du, Fuzhen Zhuang, Jia He +2

In real world machine learning applications, testing data may contain some meaningful new categories that have not been seen in labeled training data. To simultaneously recognize n…

cs.LG2019★ 29 cited

Warm Up Cold-start Advertisements: Improving CTR Predictions via Learning to Learn ID Embeddings

Feiyang Pan, Shuokai Li, Xiang Ao +2

Click-through rate (CTR) prediction has been one of the most central problems in computational advertising. Lately, embedding techniques that produce low-dimensional representation…

cs.LG2018★ 2 cited

Policy Optimization with Model-based Explorations

Feiyang Pan, Qingpeng Cai, An-Xiang Zeng +5

Model-free reinforcement learning methods such as the Proximal Policy Optimization algorithm (PPO) have successfully applied in complex decision-making problems such as Atari games…

cs.LG2018★ 21 cited

Policy Gradients for Contextual Recommendations

Feiyang Pan, Qingpeng Cai, Pingzhong Tang +2

Decision making is a challenging task in online recommender systems. The decision maker often needs to choose a contextual item at each step from a set of candidates. Contextual ba…