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12 papers · 2 filters
AdaTask: A Task-aware Adaptive Learning Rate Approach to Multi-task Learning
Enneng Yang, Junwei Pan, Ximei Wang +6
Multi-task learning (MTL) models have demonstrated impressive results in computer vision, natural language processing, and recommender systems. Even though many approaches have bee…
QuickSkill: Novice Skill Estimation in Online Multiplayer Games
Chaoyun Zhang, Kai Wang, Hao Chen +4
Matchmaking systems are vital for creating fair matches in online multiplayer games, which directly affects players' satisfactions and game experience. Most of the matchmaking syst…
Towards Communication-efficient Vertical Federated Learning Training via Cache-enabled Local Updates
Fangcheng Fu, Xupeng Miao, Jiawei Jiang +2
Vertical federated learning (VFL) is an emerging paradigm that allows different parties (e.g., organizations or enterprises) to collaboratively build machine learning models with p…
Efficient End-to-End AutoML via Scalable Search Space Decomposition
Yang Li, Yu Shen, Wentao Zhang +2
End-to-end AutoML has attracted intensive interests from both academia and industry which automatically searches for ML pipelines in a space induced by feature engineering, algorit…
BlindFL: Vertical Federated Machine Learning without Peeking into Your Data
Fangcheng Fu, Huanran Xue, Yong Cheng +2
Due to the rising concerns on privacy protection, how to build machine learning (ML) models over different data sources with security guarantees is gaining more popularity. Vertica…
Graph Attention Multi-Layer Perceptron
Wentao Zhang, Ziqi Yin, Zeang Sheng +6
Graph neural networks (GNNs) have achieved great success in many graph-based applications. However, the enormous size and high sparsity level of graphs hinder their applications un…