1 citations · 1 across the 5 of their papers we have counts for
12 papers
RMISC: A Large-scale Real-world Multivariate Corpus for Time Series Foundation Models
Qian Sun, Yong-Ming Tian, Jia-Wei Huang +2
Recent years have witnessed the emergence of multivariate modeling using time series foundation models (TSFMs), which achieve advanced zero-shot generalization. Modern multivariate…
Generalization Bounds of Spiking Neural Networks via Rademacher Complexity
Shao-Qun Zhang, Zhi-Hua Zhou
Spiking Neural Networks (SNNs) have garnered increasing attention as one of bio-inspired models due to their great potential in neuromorphic computing and sparse computation. Many…
Theoretical Investigation on Inductive Bias of Isolation Forest
Qin-Cheng Zheng, Shao-Qun Zhang, Shen-Huan Lyu +2
Isolation Forest (iForest) stands out as a widely-used unsupervised anomaly detector, primarily owing to its remarkable runtime efficiency and superior performance in large-scale t…
On the Approximation and Complexity of Deep Neural Networks to Invariant Functions
Gao Zhang, Jin-Hui Wu, Shao-Qun Zhang
Recent years have witnessed a hot wave of deep neural networks in various domains; however, it is not yet well understood theoretically. A theoretical characterization of deep neur…
On the Intrinsic Structures of Spiking Neural Networks
Shao-Qun Zhang, Jia-Yi Chen, Jin-Hui Wu +4
Recent years have emerged a surge of interest in SNNs owing to their remarkable potential to handle time-dependent and event-driven data. The performance of SNNs hinges not only on…
ARISE: ApeRIodic SEmi-parametric Process for Efficient Markets without Periodogram and Gaussianity Assumptions
Shao-Qun Zhang, Zhi-Hua Zhou
Mimicking and learning the long-term memory of efficient markets is a fundamental problem in the interaction between machine learning and financial economics to sequential data. De…