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20192022
most citedGeneralizing from a Few Examples: A Survey on Few-Shot Learning

791 citations · 963 across the 16 of their papers we have counts for

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cs.LG2021

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…

cs.LG2021★ 13 cited

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…

cs.LG2021

FedTriNet: A Pseudo Labeling Method with Three Players for Federated Semi-supervised Learning

Liwei Che, Zewei Long, Jiaqi Wang +3

Federated Learning has shown great potentials for the distributed data utilization and privacy protection. Most existing federated learning approaches focus on the supervised setti…

cs.LG2021★ 36 cited

Property-Aware Relation Networks for Few-Shot Molecular Property Prediction

Yaqing Wang, Abulikemu Abuduweili, Quanming Yao +1

Molecular property prediction plays a fundamental role in drug discovery to identify candidate molecules with target properties. However, molecular property prediction is essential…

cs.LG2020★ 10 cited

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…

cs.LG2020

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…

cs.LG2020★ 3 cited

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…

cs.LG2019★ 791 cited

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…