13 citations · 23 across the 13 of their papers we have counts for
4 papers · 1 filter
Spatio-temporal point processes with deep non-stationary kernels
Zheng Dong, Xiuyuan Cheng, Yao Xie
Point process data are becoming ubiquitous in modern applications, such as social networks, health care, and finance. Despite the powerful expressiveness of the popular recurrent n…
Online Kernel CUSUM for Change-Point Detection
Song Wei, Yao Xie
We present a computationally efficient online kernel Cumulative Sum (CUSUM) method for change-point detection that utilizes the maximum over a set of kernel statistics to account f…
Neural network-based CUSUM for online change-point detection
Tingnan Gong, Junghwan Lee, Xiuyuan Cheng +1
Change-point detection, detecting an abrupt change in the data distribution from sequential data, is a fundamental problem in statistics and machine learning. CUSUM is a popular st…
Crime Hot-Spot Modeling via Topic Modeling and Relative Density Estimation
Jonathan Zhou, Sarah Huestis-Mitchell, Xiuyuan Cheng +1
We present a method to capture groupings of similar calls and determine their relative spatial distribution from a collection of crime record narratives. We first obtain a topic di…