← Authors

Chaochao Chen

42 papers · 2018–2026 · 9 conferences · across top CS/AI conferences

Achievements

🌈 Renaissance Researcher (9) πŸƒ Academic Marathon (7) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (10) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (65) 🌍 Conference Polyglot (9) πŸ”¬ Deep Specialist (12) 🀝 Dynamic Duo (19) πŸ† Grand Slam πŸ† Keyword Champion (7) πŸ—ƒοΈ Keyword Collector (173) ⚑ Prolific Year (11) πŸš€ Conference Pioneer πŸ’Ž Century Club (38) πŸ”₯ Unstoppable (8) πŸ“ˆ Trend Setter

Conferences

AAAI (13) IJCAI (11) NIPS (8) ICML (4) JMLR (2) ACL (1) CVPR (1) EMNLP (1) ICLR (1)

Top co-authors

Xiaolin Zheng (20) Weiming Liu (17) Xinting Liao (11) Jun Zhou (9) Yuyuan Li (9) Lingjuan Lyu (6) Yanchao Tan (5) Jun Wang (5) Pengyang Zhou (5) Fan Wang (5)

Research topics

Differential Privacy (1) Privacy (1)

Keywords

federated learning (11) graph neural network (7) cross-domain recommendation (7) representation learning (6) recommendation system (4) differential privacy (4) node classification (3) machine unlearning (3) contrastive learning (3) data sparsity (3) optimal transport (3) recommender system (3) knowledge transfer (3) generative adversarial network (2) sequential recommendation (2) non-iid datum (2) graph representation (2) privacy-preserving learning (2) domain adaptation (2) transfer learning (2)

Papers

FedAU2: Attribute Unlearning for User-Level Federated Recommender Systems with Adaptive and Robust Adversarial Training AAAI 2026
Targeting Borderline Fraudsters: Multi-View Hypergraph Fraud Detection with LLM-Guided Contrastive Learning AAAI 2026
Potent but Stealthy: Rethink Profile Pollution Against Sequential Recommendation via Bi-Level Constrained Reinforcement Paradigm AAAI 2026
TOFA: Training-Free One-Shot Federated Adaptation for Vision-Language Models AAAI 2026
Efficient Source-free Unlearning via Energy-Guided Data Synthesis and Discrimination-Aware Multitask Optimization ICML 2025
Adaptive Client Sampling in Federated Learning via Online Learning with Bandit Feedback JMLR 2025
Heterogeneous Temporal Hypergraph Neural Network IJCAI 2025
DR-VAE: Debiased and Representation-enhanced Variational Autoencoder for Collaborative Recommendation AAAI 2025
Sim4Rec: Data-Free Model Extraction Attack on Sequential Recommendation AAAI 2025
LoGoFair: Post-Processing for Local and Global Fairness in Federated Learning AAAI 2025
FedGOG: Federated Graph Out-of-Distribution Generalization with Diffusion Data Exploration and Latent Embedding Decorrelation AAAI 2025
Controllable Unlearning for Image-to-Image Generative Models via $\epsilon$-Constrained Optimization ICLR 2025
FOCoOp: Enhancing Out-of-Distribution Robustness in Federated Prompt Learning for Vision-Language Models ICML 2025
Rethinking the Representation in Federated Unsupervised Learning with Non-IID Data CVPR 2024
Fine-grained Pluggable Gradient Ascent for Knowledge Unlearning in Language Models EMNLP 2024
Reducing Item Discrepancy via Differentially Private Robust Embedding Alignment for Privacy-Preserving Cross Domain Recommendation ICML 2024
One for All: A Universal Generator for Concept Unlearnability via Multi-Modal Alignment ICML 2024
Protecting Split Learning by Potential Energy Loss IJCAI 2024
FOOGD: Federated Collaboration for Both Out-of-distribution Generalization and Detection NIPS 2024
CURE4Rec: A Benchmark for Recommendation Unlearning with Deeper Influence NIPS 2024
Federated Graph Learning for Cross-Domain Recommendation NIPS 2024
UKnow: A Unified Knowledge Protocol with Multimodal Knowledge Graph Datasets for Reasoning and Vision-Language Pre-Training NIPS 2024
Intra- and Inter-group Optimal Transport for User-Oriented Fairness in Recommender Systems AAAI 2024
Learning Accurate and Bidirectional Transformation via Dynamic Embedding Transportation for Cross-Domain Recommendation AAAI 2024
SQLFlow: An Extensible Toolkit Integrating DB and AI JMLR 2023
UltraRE: Enhancing RecEraser for Recommendation Unlearning via Error Decomposition NIPS 2023
PPGenCDR: A Stable and Robust Framework for Privacy-Preserving Cross-Domain Recommendation AAAI 2023
Robust Representation Learning with Reliable Pseudo-labels Generation via Self-Adaptive Optimal Transport for Short Text Clustering ACL 2023
Federated Probabilistic Preference Distribution Modelling with Compactness Co-Clustering for Privacy-Preserving Multi-Domain Recommendation IJCAI 2023
HyperFed: Hyperbolic Prototypes Exploration with Consistent Aggregation for Non-IID Data in Federated Learning IJCAI 2023
Reducing Communication for Split Learning by Randomized Top-k Sparsification IJCAI 2023
HCFRec: Hash Collaborative Filtering via Normalized Flow with Structural Consensus for Efficient Recommendation IJCAI 2022
Vertically Federated Graph Neural Network for Privacy-Preserving Node Classification IJCAI 2022
MERIT: Learning Multi-level Representations on Temporal Graphs IJCAI 2022
Exploiting Data Sparsity in Secure Cross-Platform Social Recommendation NIPS 2021
Cross-Domain Recommendation: Challenges, Progress, and Prospects IJCAI 2021
Leveraging Distribution Alignment via Stein Path for Cross-Domain Cold-Start Recommendation NIPS 2021
Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics AAAI 2020
A Graphical and Attentional Framework for Dual-Target Cross-Domain Recommendation IJCAI 2020
Generalization in Generative Adversarial Networks: A Novel Perspective from Privacy Protection NIPS 2019
GeniePath: Graph Neural Networks with Adaptive Receptive Paths AAAI 2019
A Deep Framework for Cross-Domain and Cross-System Recommendations IJCAI 2018