15 citations · 30 across the 12 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…
Theoretical Exploration of Flexible Transmitter Model
Jin-Hui Wu, Shao-Qun Zhang, Yuan Jiang +1
Neural network models generally involve two important components, i.e., network architecture and neuron model. Although there are abundant studies about network architectures, only…
LIFE: Learning Individual Features for Multivariate Time Series Prediction with Missing Values
Zhao-Yu Zhang, Shao-Qun Zhang, Yuan Jiang +1
Multivariate time series (MTS) prediction is ubiquitous in real-world fields, but MTS data often contains missing values. In recent years, there has been an increasing interest in…
Neural Network Gaussian Processes by Increasing Depth
Shao-Qun Zhang, Fei Wang, Feng-Lei Fan
Recent years have witnessed an increasing interest in the correspondence between infinitely wide networks and Gaussian processes. Despite the effectiveness and elegance of the curr…
Towards Understanding Theoretical Advantages of Complex-Reaction Networks
Shao-Qun Zhang, Wei Gao, Zhi-Hua Zhou
Complex-valued neural networks have attracted increasing attention in recent years, while it remains open on the advantages of complex-valued neural networks in comparison with rea…
Flexible Transmitter Network
Shao-Qun Zhang, Zhi-Hua Zhou
Current neural networks are mostly built upon the MP model, which usually formulates the neuron as executing an activation function on the real-valued weighted aggregation of signa…
Bifurcation Spiking Neural Network
Shao-Qun Zhang, Zhao-Yu Zhang, Zhi-Hua Zhou
Spiking neural networks (SNNs) has attracted much attention due to its great potential of modeling time-dependent signals. The firing rate of spiking neurons is decided by control…