
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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Sketching for Sequential ChangePoint Detection
We study sequential changepoint detection using sketches (linear projec...
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Poisson Matrix Recovery and Completion
We extend the theory of lowrank matrix recovery and completion to the c...
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Poisson Matrix Completion
We extend the theory of matrix completion to the case where we make Pois...
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Sequential Sensing with Model Mismatch
We characterize the performance of sequential information guided sensing...
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Sequential Changepoint Approach for Online Community Detection
We present new algorithms for detecting the emergence of a community in ...
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InfoGreedy sequential adaptive compressed sensing
We present an informationtheoretic framework for sequential adaptive co...
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Fast Algorithm for Lowrank matrix recovery in Poisson noise
This paper describes a fast algorithm for recovering lowrank matrices f...
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Changepoint detection for highdimensional time series with missing data
This paper describes a novel approach to changepoint detection when the...
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