3 papers
physics.ed-ph2026
Building an Affordable Self-Driving Lab: Practical Machine Learning Experiments for Physics Education Using Internet-of-Things
Yang Liu, Qianjie Lei, Xiaolong He +9
Machine learning (ML) is transforming modern physics research, but practical, hands-on experience with ML techniques remains limited due to cost and complexity barriers. To address…
cs.LG2026
More Than Memory Savings: Zeroth-Order Optimization Mitigates Forgetting in Continual Learning
Wanhao Yu, Zheng Wang, Shuteng Niu +2
Zeroth-order (ZO) optimization has gained attention as a memory-efficient alternative to first-order (FO) methods, particularly in settings where gradient computation is expensive…
cs.LG2026
Rethinking Continual Learning with Progressive Neural Collapse
Zheng Wang, Wanhao Yu, Li Yang +1
Continual Learning (CL) seeks to build an agent that can continuously learn a sequence of tasks, where a key challenge, namely Catastrophic Forgetting, persists due to the potentia…