151 citations · 632 across the 84 of their papers we have counts for
8 papers · 1 filter
Learning Temporal Point Processes via Reinforcement Learning
Shuang Li, Shuai Xiao, Shixiang Zhu +3
Social goods, such as healthcare, smart city, and information networks, often produce ordered event data in continuous time. The generative processes of these event data can be ver…
Sequential Subspace Change-Point Detection
Liyan Xie, Yao Xie, George V. Moustakides
We consider the online monitoring of multivariate streaming data for changes that are characterized by an unknown subspace structure manifested in the covariance matrix. In particu…
An Approximation Algorithm for training One-Node ReLU Neural Network
Santanu S. Dey, Guanyi Wang, Yao Xie
Training a one-node neural network with ReLU activation function (One-Node-ReLU) is a fundamental optimization problem in deep learning. In this paper, we begin with proving the NP…
First-order optimal sequential subspace change-point detection
Liyan Xie, George V. Moustakides, Yao Xie
We consider the sequential change-point detection problem of detecting changes that are characterized by a subspace structure. Such changes are frequent in high-dimensional streami…
Crime Event Embedding with Unsupervised Feature Selection
Shixiang Zhu, Yao Xie
We present a novel event embedding algorithm for crime data that can jointly capture time, location, and the complex free-text component of each event. The embedding is achieved by…
Robust Hypothesis Testing Using Wasserstein Uncertainty Sets
Rui Gao, Liyan Xie, Yao Xie +1
We develop a novel computationally efficient and general framework for robust hypothesis testing. The new framework features a new way to construct uncertainty sets under the null…