4 papers
Test Case Prioritization for DNNs via Neural Collapse Instability
Chunyu Liu, Mingyuan Li, Yang Li +4
With the widespread deployment of deep neural networks (DNNs) in safety-critical domains, reducing the cost of model validation under limited testing budgets has become increasingl…
QSEA: Quantum Self-supervised Learning with Entanglement Augmentation
Lingxiao Li, Xiaohui Ni, Jing Li +2
As an unsupervised feature representation paradigm, Self-Supervised Learning (SSL) uses the intrinsic structure of data to extract meaningful features without relying on manual ann…
Quantum Multi-view Kernel Learning with Local Information
Jing Li, Yanqi Song, Sujuan Qin +1
Kernel methods serve as powerful tools to capture nonlinear patterns behind data in machine learning. The quantum kernel, integrating kernel theory with quantum computing, has attr…
Proactively incremental-learning QAOA
Lingxiao Li, Jing Li, Yanqi Song +3
Solving optimization problems with high performance is the target of existing works of Quantum Approximate Optimization Algorithm (QAOA). With this intention, we propose an advance…