3 citations · 4 across the 4 of their papers we have counts for
4 papers
MECPformer: Multi-estimations Complementary Patch with CNN-Transformers for Weakly Supervised Semantic Segmentation
Chunmeng Liu, Guangyao Li, Yao Shen +1
The initial seed based on the convolutional neural network (CNN) for weakly supervised semantic segmentation always highlights the most discriminative regions but fails to identify…
Heterogeneous Federated Knowledge Graph Embedding Learning and Unlearning
Xiangrong Zhu, Guangyao Li, Wei Hu
Federated Learning (FL) recently emerges as a paradigm to train a global machine learning model across distributed clients without sharing raw data. Knowledge Graph (KG) embedding…
EventEA: Benchmarking Entity Alignment for Event-centric Knowledge Graphs
Xiaobin Tian, Zequn Sun, Guangyao Li +1
Entity alignment is to find identical entities in different knowledge graphs (KGs) that refer to the same real-world object. Embedding-based entity alignment techniques have been d…
I Know What You Do Not Know: Knowledge Graph Embedding via Co-distillation Learning
Yang Liu, Zequn Sun, Guangyao Li +1
Knowledge graph (KG) embedding seeks to learn vector representations for entities and relations. Conventional models reason over graph structures, but they suffer from the issues o…