492 citations · 1.2k across the 50 of their papers we have counts for
50 papers
Mining Minority-class Examples With Uncertainty Estimates
Gursimran Singh, Lingyang Chu, Lanjun Wang +3
In the real world, the frequency of occurrence of objects is naturally skewed forming long-tail class distributions, which results in poor performance on the statistically rare cla…
Knowledge-Enhanced Hierarchical Graph Transformer Network for Multi-Behavior Recommendation
Lianghao Xia, Chao Huang, Yong Xu +5
Accurate user and item embedding learning is crucial for modern recommender systems. However, most existing recommendation techniques have thus far focused on modeling users' prefe…
AsySQN: Faster Vertical Federated Learning Algorithms with Better Computation Resource Utilization
Qingsong Zhang, Bin Gu, Cheng Deng +4
Vertical federated learning (VFL) is an effective paradigm of training the emerging cross-organizational (e.g., different corporations, companies and organizations) collaborative l…
Learning from Multiple Noisy Augmented Data Sets for Better Cross-Lingual Spoken Language Understanding
Yingmei Guo, Linjun Shou, Jian Pei +4
Lack of training data presents a grand challenge to scaling out spoken language understanding (SLU) to low-resource languages. Although various data augmentation approaches have be…
Achieving Model Fairness in Vertical Federated Learning
Changxin Liu, Zhenan Fan, Zirui Zhou +4
Vertical federated learning (VFL) has attracted greater and greater interest since it enables multiple parties possessing non-overlapping features to strengthen their machine learn…
Auto-Split: A General Framework of Collaborative Edge-Cloud AI
Amin Banitalebi-Dehkordi, Naveen Vedula, Jian Pei +3
In many industry scale applications, large and resource consuming machine learning models reside in powerful cloud servers. At the same time, large amounts of input data are collec…