62 citations · 250 across the 38 of their papers we have counts for
11 papers · 1 filter
Two Wrongs Don't Make a Right: Combating Confirmation Bias in Learning with Label Noise
Mingcai Chen, Hao Cheng, Yuntao Du +3
Noisy labels damage the performance of deep networks. For robust learning, a prominent two-stage pipeline alternates between eliminating possible incorrect labels and semi-supervis…
RMNet: Equivalently Removing Residual Connection from Networks
Fanxu Meng, Hao Cheng, Jiaxin Zhuang +2
Although residual connection enables training very deep neural networks, it is not friendly for online inference due to its multi-branch topology. This encourages many researchers…
Learning with Noisy Labels Revisited: A Study Using Real-World Human Annotations
Jiaheng Wei, Zhaowei Zhu, Hao Cheng +3
Existing research on learning with noisy labels mainly focuses on synthetic label noise. Synthetic noise, though has clean structures which greatly enabled statistical analyses, of…
Mitigating Memorization of Noisy Labels via Regularization between Representations
Hao Cheng, Zhaowei Zhu, Xing Sun +1
Designing robust loss functions is popular in learning with noisy labels while existing designs did not explicitly consider the overfitting property of deep neural networks (DNNs).…
Disentangled Feature Representation for Few-shot Image Classification
Hao Cheng, Yufei Wang, Haoliang Li +2
Learning the generalizable feature representation is critical for few-shot image classification. While recent works exploited task-specific feature embedding using meta-tasks for f…
Keypoints-Based Deep Feature Fusion for Cooperative Vehicle Detection of Autonomous Driving
Yunshuang Yuan, Hao Cheng, Monika Sester
Sharing collective perception messages (CPM) between vehicles is investigated to decrease occlusions so as to improve the perception accuracy and safety of autonomous driving. Howe…
Bayesian Analysis of Multivariate Matched Proportions with Sparse Response
Mark J. Meyer, Haobo Cheng, Katherine Hobbs Knutson
Multivariate matched proportions (MMP) data appears in a variety of contexts including post-market surveillance of adverse events in pharmaceuticals, disease classification, and ag…
Leopard: Towards High Throughput-Preserving BFT for Large-scale Systems
Kexin Hu, Kaiwen Guo, Qiang Tang +3
With the emergence of large-scale decentralized applications, a scalable and efficient Byzantine Fault Tolerant (BFT) protocol of hundreds of replicas is desirable. Although the th…
Measurements of Dy() at energies relevant for astrophysical process
Hao Cheng, Bao-Hua Sun, Li-Hua Zhu +20
Rare information on photodisintegration reactions of nuclei with mass numbers at astrophysical conditions impedes our understanding of the origin of -nuclei. Exp…
Orientation to Pose: Continuum Robots Shape Sensing Based on Piecewise Polynomial Curvature Model
Hao Cheng, Hongji Shang, Bin Lan +3
Continuum robots are typically slender and flexible with infinite freedoms in theory, which poses a challenge for their control and application. The shape sensing of continuum robo…
Joint Dimensionality Reduction for Separable Embedding Estimation
Yanjun Li, Bihan Wen, Hao Cheng +1
Low-dimensional embeddings for data from disparate sources play critical roles in multi-modal machine learning, multimedia information retrieval, and bioinformatics. In this paper,…