← Search

Ye Su

3 accepted papers

2026

Deep Multi-view Graph Clustering via Attribute-aware Bidirectional Structural Refinement and Pseudo-label Guided Multi-level Fusion

ICML 2026poster

Deep multi-view graph clustering (DMGC) typically leverages graph neural networks for representation learning, but most existing methods excessively depend on local and static graph structures and only utilize simplistic cross-view fusion strategies. To this end, this paper proposes **A**ttribute-aw…

Cited by 0SourceScholar
2026

ITBoost: Information-Theoretic Trust for Robust Boosting

IJCAI 2026

Gradient boosting remains a strong and widely used method for tabular data learning, but its performance often degrades when training labels are noisy. This behavior is largely related to the way boosting algorithms emphasize samples with large gradients, without explicitly accounting for whether su

Cited by 0Scholar
2019

Robot-Assisted Training in Laparoscopy Using Deep Reinforcement Learning

RA-L 2019

Minimally invasive surgery (MIS) is increasingly becoming a vital method of reducing surgical trauma and significantly improving postoperative recovery. However, skillful handling of surgical instruments used in MIS, especially for laparoscopy, requires a long period of training and depends highly o

Cited by 51SourceScholar