
DataDriven Optimization for Police Zone Design
We present a datadriven optimization framework for redesigning police p...
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Online HighDimensional ChangePoint Detection using Topological Data Analysis
Topological Data Analysis (TDA) is a rapidly growing field, which studie...
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Twosample Test with Kernel Projected Wasserstein Distance
We develop a kernel projected Wasserstein distance for the twosample te...
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Optimality of Graph Scanning Statistic for Online Community Detection
Sequential changepoint detection for graphs is a fundamental problem fo...
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Sequential changepoint detection for mutually exciting point processes over networks
We present a new CUSUM procedure for sequentially detecting changepoint...
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Balanced Districting on Grid Graphs with Provable Compactness and Contiguity
Given a graph G = (V,E) with vertex weights w(v) and a desired number of...
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Solar Radiation Anomaly Events Modeling Using SpatialTemporal Mutually Interactive Processes
Modeling and predicting solar events, in particular, the solar ramping e...
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Inferring serial correlation with dynamic backgrounds
Sequential data with serial correlation and an unknown, unstructured, an...
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Bayesian Uncertainty Quantification for Lowrank Matrix Completion
We consider the problem of uncertainty quantification for an unknown low...
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Tensor Kernel Recovery for SpatioTemporal Hawkes Processes
We estimate the general influence functions for spatiotemporal Hawkes p...
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Twosample Test using Projected Wasserstein Distance: Breaking the Curse of Dimensionality
We develop a projected Wasserstein distance for the twosample test, a f...
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Sequential Change Detection by Optimal Weighted ℓ_2 Divergence
We present a new nonparametric statistics, called the weighted ℓ_2 dive...
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Conformal prediction interval for dynamic timeseries
We develop a method to build distributionfree prediction intervals in b...
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Highresolution Spatiotemporal Model for Countylevel COVID19 Activity in the U.S
We present an interpretable highresolution spatiotemporal model to est...
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GoodnessofFit Test for SelfExciting Processes
Recently there have been many research efforts in developing generative ...
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Uncertainty Quantification for Inferring Hawkes Networks
Multivariate Hawkes processes are commonly used to model streaming netwo...
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Distributionally Robust kNearest Neighbors for FewShot Learning
Learning a robust classifier from a few samples remains a key challenge ...
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SpatioTemporal Point Processes with Attention for Traffic Congestion Event Modeling
We present a novel framework for modeling traffic congestion events over...
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DataDriven Optimization for Police Beat Design in South Fulton, Georgia
We redesign the police patrol beat in South Fulton, Georgia, in collabor...
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Convex Recovery of Marked SpatioTemporal Point Processes
We present a multidimensional Bernoulli process model for spatialtempo...
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Convex Parameter Recovery for Interacting Marked Processes
We introduce a new general modeling approach for multivariate discrete e...
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Deep Attention SpatioTemporal Point Processes
We present a novel attentionbased sequential model for mutually depende...
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CheXplain: Enabling Physicians to Explore and UnderstandDataDriven, AIEnabled Medical Imaging Analysis
The recent development of datadriven AI promises to automate medical di...
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Adversarial Anomaly Detection for Marked SpatioTemporal Streaming Data
Spatiotemporal event data are becoming increasingly available in a wide...
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Online Community Detection by Spectral CUSUM
We present an online community change detection algorithm called spectra...
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Goodnessoffit tests on manifolds
We develop a general theory for the goodnessoffit test to nonlinear m...
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Reinforcement Learning of SpatioTemporal Point Processes
Spatiotemporal event data is ubiquitous in various applications, such a...
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Deep ZeroShot Learning for Scene Sketch
We introduce a novel problem of scene sketch zeroshot learning (SSZSL),...
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Outlining the Design Space of Explainable Intelligent Systems for Medical Diagnosis
The adoption of intelligent systems creates opportunities as well as cha...
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Crime Linkage Detection by SpatialTemporalTextual Point Processes
Crimes emerge out of complex interactions of behaviors and situations; t...
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Learning Transformation Synchronization
Reconstructing the 3D model of a physical object typically requires us t...
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Asynchronous MultiSensor ChangePoint Detection for Seismic Tremors
We consider the sequential changepoint detection for asynchronous multi...
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Learning Temporal Point Processes via Reinforcement Learning
Social goods, such as healthcare, smart city, and information networks, ...
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Sequential Subspace Changepoint Detection
We consider the sequential changepoint detection problem of detecting ch...
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Firstorder optimal sequential subspace changepoint detection
We consider the sequential changepoint detection problem of detecting c...
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Crime Event Embedding with Unsupervised Feature Selection
We present a novel event embedding algorithm for crime data that can joi...
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Robust Hypothesis Testing Using Wasserstein Uncertainty Sets
We develop a novel computationally efficient and general framework for r...
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Nearly Optimal Adaptive Procedure for PiecewiseStationary Bandit: a ChangePoint Detection Approach
Multiarmed bandit (MAB) is a class of online learning problems where a ...
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Matrix completion with deterministic pattern  a geometric perspective
We consider the matrix completion problem with a deterministic pattern o...
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Maximum entropy lowrank matrix recovery
We propose a novel, informationtheoretic method, called MaxEnt, for eff...
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Crime incidents embedding using restricted Boltzmann machines
We present a new approach for detecting related crime series, by unsuper...
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Sequential detection of lowrank changes using extreme eigenvalues
We study the problem of detecting an abrupt change to the signal covaria...
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DataDriven Threshold Machine: Scan Statistics, ChangePoint Detection, and Extreme Bandits
We present a novel distributionfree approach, the datadriven threshold...
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Sequential LowRank Change Detection
Detecting emergence of a lowrank signal from highdimensional data is a...
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Detecting weak changes in dynamic events over networks
Large volume of networked streaming event data are becoming increasingly...
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Online Supervised Subspace Tracking
We present a framework for supervised subspace tracking, when there are ...
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Sequential Information Guided Sensing
We study the value of information in sequential compressed sensing by ch...
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MultiSensor Slope Change Detection
We develop a mixture procedure for multisensor systems to monitor data ...
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Scan BStatistic for Kernel ChangePoint Detection
Detecting the emergence of an abrupt changepoint is a classic problem i...
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Categorical Matrix Completion
We consider the problem of completing a matrix with categoricalvalued e...
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