k-HyperEdge Medoids for Clustering Ensemble

Feijiang Li, Jieting Wang, Liuya zhang, Yuhua Qian, Shuai jin, Tao Yan, Liang Du

lustering ensemble has been a popular research topic in data science due to its ability to improve the robustness of the single clustering method.

AAAI'25

Neural Collapse To Multiple Centers For Imbalanced Data

闫泓任，钱宇华*，彭甫镕，罗嘉琛，朱哲清，李飞江

Neural Collapse (NC) was a recently discovered phenomenon that the output features and the classifier weights of the neural network converge to optimal geometric structures at the Terminal Phase of Training (TPT) under various losses.

NeurIPS '2024

A Progressive Skip Reasoning Fusion Method for Multi-Modal Classification

Qian Guo, Xinyan Liang, Yuhua Qian, Zhihua Cui, Jie Wen

Abstract In multi-modal classification tasks, a good fusion algorithm can effectively integrate and process multi-modal data, thereby significantly improving its performance.

ACM Multimedia 2024

Robotic Grasp Detection Using Structure Prior Attention and Multiscale Features

Lu Chen, Mingdi Niu, Jing Yang, Yuhua Qian, Zhuomao Li, , Keqi Wang, Tao Yan, Panfeng Huang

IEEE Transactions on Systems, Man, and Cybernetics: Systems

DC-NAS: Divide-and-Conquer Neural Architecture Search for Multi-Modal Classification

Xinyan Liang, Pinhan Fu, Qian Guo, Keyin Zheng, Yuhua Qian

Neural architecture search-based multi-modal classification (NAS-MMC) methods can individually obtain the optimal classifier for different multi-modal data sets in an automatic manner.

AAAI'24