no code implementations • 26 Mar 2024 • Shuyi Chen, Shixiang Zhu
We introduce a novel data pre-processing algorithm, Orthogonal to Bias (OB), designed to remove the influence of a group of continuous sensitive variables, thereby facilitating counterfactual fairness in machine learning applications.
no code implementations • 27 Oct 2023 • Wenqian Xing, Jungho Lee, Chong Liu, Shixiang Zhu
This approach leverages a conditional variational autoencoder to learn the distribution of feasible decisions, enabling a two-way mapping between the original decision space and a simplified, constraint-free latent space.
no code implementations • 5 Oct 2023 • Song Wei, Xiangrui Kong, Alinson Santos Xavier, Shixiang Zhu, Yao Xie, Feng Qiu
Energy justice is a growing area of interest in interdisciplinary energy research.
no code implementations • 14 Jun 2023 • Shuyi Chen, Kaize Ding, Shixiang Zhu
Graph neural networks have shown impressive capabilities in solving various graph learning tasks, particularly excelling in node classification.
no code implementations • 25 May 2023 • Shenghao Wu, Wenbin Zhou, Minshuo Chen, Shixiang Zhu
Estimating the counterfactual outcome of treatment is essential for decision-making in public health and clinical science, among others.
no code implementations • 21 May 2023 • Zheng Dong, Zekai Fan, Shixiang Zhu
To address this challenge, this study proposes a novel event-generation framework for modeling point processes with high-dimensional marks.
1 code implementation • ICLR 2022 • Shixiang Zhu, Haoyun Wang, Zheng Dong, Xiuyuan Cheng, Yao Xie
In this paper, we introduce a novel and general neural network-based non-stationary influence kernel with high expressiveness for handling complex discrete events data while providing theoretical performance guarantees.
no code implementations • 31 May 2021 • Shixiang Zhu, Alexander Bukharin, Liyan Xie, Khurram Yamin, Shihao Yang, Pinar Keskinocak, Yao Xie
Recently, the Centers for Disease Control and Prevention (CDC) has worked with other federal agencies to identify counties with increasing coronavirus disease 2019 (COVID-19) incidence (hotspots) and offers support to local health departments to limit the spread of the disease.
no code implementations • 18 Apr 2021 • Josh Kacher, Yao Xie, Sven P. Voigt, Shixiang Zhu, Henry Yuchi, Jordan Key, Surya R. Kalidindi
Transmission Electron Microscopy (TEM) is a powerful tool for imaging material structure and characterizing material chemistry.
no code implementations • 30 Mar 2021 • Shixiang Zhu, He Wang, Yao Xie
By analyzing data before and after the zone redesign, we show that the new design has reduced the response time to high priority 911 calls by 5. 8\% and the imbalance of police workload among different zones by 43\%.
no code implementations • 9 Feb 2021 • Cyrus Hettle, Shixiang Zhu, Swati Gupta, Yao Xie
Given a graph $G = (V, E)$ with vertex weights $w(v)$ and a desired number of parts $k$, the goal in graph partitioning problems is to partition the vertex set V into parts $V_1,\ldots, V_k$.
graph partitioning Data Structures and Algorithms Combinatorics Optimization and Control
no code implementations • 16 Jun 2020 • Song Wei, Shixiang Zhu, Minghe Zhang, Yao Xie
Recently there have been many research efforts in developing generative models for self-exciting point processes, partly due to their broad applicability for real-world applications.
no code implementations • 7 Jun 2020 • Shixiang Zhu, Liyan Xie, Minghe Zhang, Rui Gao, Yao Xie
When the samples are limited, robustness is especially crucial to ensure the generalization capability of the classifier.
no code implementations • 15 May 2020 • Shixiang Zhu, Ruyi Ding, Minghe Zhang, Pascal Van Hentenryck, Yao Xie
We present a novel framework for modeling traffic congestion events over road networks.
no code implementations • 17 Feb 2020 • Shixiang Zhu, Minghe Zhang, Ruyi Ding, Yao Xie
We present a novel attention-based model for discrete event data to capture complex non-linear temporal dependence structures.
no code implementations • 21 Oct 2019 • Shixiang Zhu, Henry Shaowu Yuchi, Minghe Zhang, Yao Xie
We consider the sequential anomaly detection problem in the one-class setting when only the anomalous sequences are available and propose an adversarial sequential detector by solving a minimax problem to find an optimal detector against the worst-case sequences from a generator.
1 code implementation • 13 Jun 2019 • Shixiang Zhu, Shuang Li, Zhigang Peng, Yao Xie
We present a novel Neural Embedding Spatio-Temporal (NEST) point process model for spatio-temporal discrete event data and develop an efficient imitation learning (a type of reinforcement learning) based approach for model fitting.
no code implementations • 1 Feb 2019 • Shixiang Zhu, Yao Xie
We propose a new statistical modeling framework for {\it spatio-temporal-textual} data and demonstrate its usage on crime linkage detection.
no code implementations • NeurIPS 2018 • Shuang Li, Shuai Xiao, Shixiang Zhu, Nan Du, Yao Xie, Le Song
Social goods, such as healthcare, smart city, and information networks, often produce ordered event data in continuous time.
no code implementations • 15 Jun 2018 • Shixiang Zhu, Yao Xie
Using numerical experiments on a large-scale crime dataset, we show that our regularized RBMs can achieve better event embedding and the selected features are highly interpretable from human understanding.
no code implementations • 28 Oct 2017 • Shixiang Zhu, Yao Xie
We present a new approach for detecting related crime series, by unsupervised learning of the latent feature embeddings from narratives of crime record via the Gaussian-Bernoulli Restricted Boltzmann Machines (RBM).