Guihai Chen

Toward Understanding the Influence of Individual Clients in Federated Learning

2021 · Proceedings of the AAAI Conference on Artificial Intelligence

Federated learning allows mobile clients to jointly train a global model without sending their private data to a central server. Extensive works have studied the performance guarantee of the global model, however, it is still …

Seq2Bubbles

2021

User behavior sequences contain rich information about user interests and are exploited to predict user's future clicking in sequential recommendation. Existing approaches, especially recently proposed deep learning models, often embed a sequence of clicked items …

<i>MHRR</i>: MOOCs Recommender Service With Meta Hierarchical Reinforced Ranking

2023 · IEEE Transactions on Services Computing

The exponential growth of Massive Open Online Courses (MOOCs) surges the needs of advanced models for personalized Online Education Services (OES). Existing solutions successfully recommend MOOCs courses via deep learning models, they however generate weak …

Enabling Virtual Priority in Data Center Congestion Control

2025

In data center networks, various types of traffic with strict performance requirements operate simultaneously, necessitating effective isolation and scheduling through priority queues. However, most switches support only around ten priority queues. Virtual priority can address …

Collaborative Learning of On-Device Small Model and Cloud-Based Large Model: Advances and Future Directions

2025 · arXiv (Cornell University)

The conventional cloud-based large model learning framework is increasingly constrained by latency, cost, personalization, and privacy concerns. In this survey, we explore an emerging paradigm: collaborative learning between on-device small model and cloud-based large model, …

Channel-masked Asymmetric Distribution Matching for Cross-Domain Generalized Dataset Distillation

2026 · Proceedings of the AAAI Conference on Artificial Intelligence

Dataset distillation has achieved remarkable progress as an effective approach for data compression. However, real-world data often comes from diverse domains, leading to potential mismatches between the domains of synthesized images and those of the …

Dual Graph Attention Networks for Deep Latent Representation of Multifaceted Social Effects in Recommender Systems

2019

Social recommendation leverages social information to solve data sparsity and cold-start problems in traditional collaborative filtering methods. However, most existing models assume that social effects from friend users are static and under the forms of …