58 citations · 87 across the 9 of their papers we have counts for
6 papers · 1 filter
Exploring the Common Principal Subspace of Deep Features in Neural Networks
Haoran Liu, Haoyi Xiong, Yaqing Wang +3
We find that different Deep Neural Networks (DNNs) trained with the same dataset share a common principal subspace in latent spaces, no matter in which architectures (e.g., Convolu…
FedCon: A Contrastive Framework for Federated Semi-Supervised Learning
Zewei Long, Jiaqi Wang, Yaqing Wang +2
Federated Semi-Supervised Learning (FedSSL) has gained rising attention from both academic and industrial researchers, due to its unique characteristics of co-training machine lear…
FedSiam: Towards Adaptive Federated Semi-Supervised Learning
Zewei Long, Liwei Che, Yaqing Wang +5
Federated learning (FL) has emerged as an effective technique to co-training machine learning models without actually sharing data and leaking privacy. However, most existing FL me…
A Scalable, Adaptive and Sound Nonconvex Regularizer for Low-rank Matrix Completion
Yaqing Wang, Quanming Yao, James T. Kwok
Matrix learning is at the core of many machine learning problems. A number of real-world applications such as collaborative filtering and text mining can be formulated as a low-ran…
Decomposed Adversarial Learned Inference
Alexander Hanbo Li, Yaqing Wang, Changyou Chen +1
Effective inference for a generative adversarial model remains an important and challenging problem. We propose a novel approach, Decomposed Adversarial Learned Inference (DALI), w…
Generalizing from a Few Examples: A Survey on Few-Shot Learning
Yaqing Wang, Quanming Yao, James Kwok +1
Machine learning has been highly successful in data-intensive applications but is often hampered when the data set is small. Recently, Few-Shot Learning (FSL) is proposed to tackle…