28 citations · 108 across the 18 of their papers we have counts for
18 papers
Multi-Teacher Knowledge Distillation For Text Image Machine Translation
Cong Ma, Yaping Zhang, Mei Tu +3
Text image machine translation (TIMT) has been widely used in various real-world applications, which translates source language texts in images into another target language sentenc…
E2TIMT: Efficient and Effective Modal Adapter for Text Image Machine Translation
Cong Ma, Yaping Zhang, Mei Tu +3
Text image machine translation (TIMT) aims to translate texts embedded in images from one source language to another target language. Existing methods, both two-stage cascade and o…
Research on Efficient Fuzzy Clustering Method Based on Local Fuzzy Granular balls
Jiang Xie, Qiao Deng, Shuyin Xia +3
In recent years, the problem of fuzzy clustering has been widely concerned. The membership iteration of existing methods is mostly considered globally, which has considerable probl…
Boosting Semi-Supervised 3D Object Detection with Semi-Sampling
Xiaopei Wu, Yang Zhao, Liang Peng +6
Current 3D object detection methods heavily rely on an enormous amount of annotations. Semi-supervised learning can be used to alleviate this issue. Previous semi-supervised 3D obj…
Improving End-to-End Text Image Translation From the Auxiliary Text Translation Task
Cong Ma, Yaping Zhang, Mei Tu +4
End-to-end text image translation (TIT), which aims at translating the source language embedded in images to the target language, has attracted intensive attention in recent resear…
Turning to a Teacher for Timestamp Supervised Temporal Action Segmentation
Yang Zhao, Yan Song
Temporal action segmentation in videos has drawn much attention recently. Timestamp supervision is a cost-effective way for this task. To obtain more information to optimize the mo…
Randomized Sharpness-Aware Training for Boosting Computational Efficiency in Deep Learning
Yang Zhao, Hao Zhang, Xiuyuan Hu
By driving models to converge to flat minima, sharpness-aware learning algorithms (such as SAM) have shown the power to achieve state-of-the-art performances. However, these algori…
Neighborhood Region Smoothing Regularization for Finding Flat Minima In Deep Neural Networks
Yang Zhao, Hao Zhang
Due to diverse architectures in deep neural networks (DNNs) with severe overparameterization, regularization techniques are critical for finding optimal solutions in the huge hypot…
Penalizing Gradient Norm for Efficiently Improving Generalization in Deep Learning
Yang Zhao, Hao Zhang, Xiuyuan Hu
How to train deep neural networks (DNNs) to generalize well is a central concern in deep learning, especially for severely overparameterized networks nowadays. In this paper, we pr…
Estimating the Generalization in Deep Neural Networks via Sparsity
Yang Zhao, Hao Zhang
Generalization is the key capability for deep neural networks (DNNs). However, it is challenging to give a reliable measure of the generalization ability of a DNN via only its natu…
Quantitative Performance Assessment of CNN Units via Topological Entropy Calculation
Yang Zhao, Hao Zhang
Identifying the status of individual network units is critical for understanding the mechanism of convolutional neural networks (CNNs). However, it is still challenging to reliably…
A Comprehensive Survey of 6G Wireless Communications
Yang Zhao, Wenchao Zhai, Jun Zhao +4
While fifth-generation (5G) communications are being rolled out worldwide, sixth-generation (6G) communications have attracted much attention from both the industry and the academi…
Role Taxonomy of Units in Deep Neural Networks
Yang Zhao, Hao Zhang, Xiuyuan Hu
Identifying the role of network units in deep neural networks (DNNs) is critical in many aspects including giving understandings on the mechanisms of DNNs and building basic connec…
A Survey of 6G Wireless Communications: Emerging Technologies
Yang Zhao, Jun Zhao, Wenchao Zhai +3
While fifth-generation (5G) communications are being rolled out around the world, sixth-generation (6G) communications have attracted much attention from both the industry and acad…
Feature Quantization Improves GAN Training
Yang Zhao, Chunyuan Li, Ping Yu +2
The instability in GAN training has been a long-standing problem despite remarkable research efforts. We identify that instability issues stem from difficulties of performing featu…
Dual-discriminator GAN: A GAN way of profile face recognition
Xinyu Zhang, Yang Zhao, Hao Zhang
A wealth of angle problems occur when facial recognition is performed: At present, the feature extraction network presents eigenvectors with large differences between the frontal f…
Self-Adversarially Learned Bayesian Sampling
Yang Zhao, Jianyi Zhang, Changyou Chen
Scalable Bayesian sampling is playing an important role in modern machine learning, especially in the fast-developed unsupervised-(deep)-learning models. While tremendous progresse…
Variance Reduction in Stochastic Particle-Optimization Sampling
Jianyi Zhang, Yang Zhao, Changyou Chen
Stochastic particle-optimization sampling (SPOS) is a recently-developed scalable Bayesian sampling framework that unifies stochastic gradient MCMC (SG-MCMC) and Stein variational…