activity
20162022
most citedCurriculum Audiovisual Learning

33 citations · 152 across the 28 of their papers we have counts for

collaborators

31 papers

cs.LG202122 cited

SenseMag: Enabling Low-Cost Traffic Monitoring using Non-invasive Magnetic Sensing

Kafeng Wang, Haoyi Xiong, Jie Zhang +3

The operation and management of intelligent transportation systems (ITS), such as traffic monitoring, relies on real-time data aggregation of vehicular traffic information, includi…

cs.LG2021

AgFlow: Fast Model Selection of Penalized PCA via Implicit Regularization Effects of Gradient Flow

Haiyan Jiang, Haoyi Xiong, Dongrui Wu +2

Principal component analysis (PCA) has been widely used as an effective technique for feature extraction and dimension reduction. In the High Dimension Low Sample Size (HDLSS) sett…

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

Cross-Model Consensus of Explanations and Beyond for Image Classification Models: An Empirical Study

Xuhong Li, Haoyi Xiong, Siyu Huang +2

Existing interpretation algorithms have found that, even deep models make the same and right predictions on the same image, they might rely on different sets of input features for…

cs.CV2021

Semi-Supervised Active Learning with Temporal Output Discrepancy

Siyu Huang, Tianyang Wang, Haoyi Xiong +2

While deep learning succeeds in a wide range of tasks, it highly depends on the massive collection of annotated data which is expensive and time-consuming. To lower the cost of dat…

q-bio.QM20212 cited

Structure-aware Interactive Graph Neural Networks for the Prediction of Protein-Ligand Binding Affinity

Shuangli Li, Jingbo Zhou, Tong Xu +6

Drug discovery often relies on the successful prediction of protein-ligand binding affinity. Recent advances have shown great promise in applying graph neural networks (GNNs) for b…