Pinhan Fu

EvoFMVC: Trusted Federated Multi-View Clustering with Evolutionary Fusion

With the growing demand for decentralized collaborative analysis of privacy-sensitive data, federated multi-view clustering (FMVC) has attracted widespread attention due to its ability to balance privacy protection and collaborative modeling. However, current methods still face the following challen

When Attention Betrays: Erasing Backdoor Attacks in Robotic Policies by Reconstructing Visual Tokens

Trusted Multi-View Classification via Evolutionary Multi-View Fusion

Multi-view classification based on the Dempster-Shafer theory is widely recognized for its reliability in safety-critical domains with multi-view data. However, the adoption of a late fusion strategy constrains information interaction among views, thereby leading to suboptimal utilization of multi-v…

Core-Structures-Guided Multi-Modal Classification Neural Architecture Search

The multi-modal classification methods based on neural architecture search (NAS-MMC) can automatically learn a satisfied classifier from a given multi-modal search space. However, as the number of multi-modal features and fusion operators increases, the complexity of search space has increased drama…

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

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. However, most existing NAS-MMC methods are dramatically time consuming due to the requirement for training and eval…