4 papers
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…
Quantum Knowledge Distillation for Large Language Models
Lingxiao Li, Yihao Wang, Jiacheng Fan +4
As foundational tools in natural language processing, Large Language Models (LLMs) have immense parameter scales, which makes deployment and inference increasingly prohibitive, esp…
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…