5 papers indexed
Ke Sun, Xinyuan Zhang, Xinwu Qian
Learning-based methods for the traveling salesman problem (TSP) are often evaluated through the tours produced after decoding or search, but the learned object itself frequently lives in a surrogate space such as heatmaps, assignments, construction policies, or search-guidance sc…
He Liu, Changtao Miao, Xinjie Yang, Tianle Song, Yin Wu, Junchi Chen, et al.
Large language models deployed in open-world applications require safety guardrails that are both robust to complex risks and efficient enough for low-latency runtime moderation. Existing guardrails face a practical trade-off between lightweight classification-based models, which…
Jianqing Jia, Yi Gong, Xinyuan Zhang, Jichen Chai, Yichen Ding, Yifei Lou
We investigate volumetric reconstruction for compressive sensing light-sheet microscopy (CS-LSM), where fast volumetric imaging is achieved by encoding multiple axial planes into each camera exposure. To recover the underlying volume from highly multiplexed measurements, we propo…
Jingyi Chen, Xinyuan Zhang, Xinwu Qian
Combinatorial optimization (CO) problems are difficult because certifiable discrete structure induces exponential search. One needs to search over the set exponentially many candidates to certify optimality, however, the structural feasibility of a path, packing, or cover can be…
Zhenxia Xue, Yan Wang, Yuwen Ren, Xinyuan Zhang
As a novel learning algorithm for feedforward neural networks, the twin extreme learning machine (TELM) boasts advantages such as simple structure, few parameters, low complexity, and excellent generalization performance. However, it employs the squared L2-norm metric and an unbo…