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07/02/2023
MissDiff: Training Diffusion Models on Tabular Data with Missing Values
The diffusion model has shown remarkable performance in modeling data di...
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06/02/2023
Neural Differential Recurrent Neural Network with Adaptive Time Steps
The neural Ordinary Differential Equation (ODE) model has shown success ...
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10/18/2022
Improving Adversarial Robustness by Contrastive Guided Diffusion Process
Synthetic data generation has become an emerging tool to help improve th...
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06/14/2022
Window-Limited CUSUM for Sequential Change Detection
We study the parametric online changepoint detection problem, where the ...
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04/27/2022
Minimax Robust Quickest Change Detection using Wasserstein Ambiguity Sets
We study the robust quickest change detection under unknown pre- and pos...
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03/08/2022
PERCEPT: a new online change-point detection method using topological data analysis
Topological data analysis (TDA) provides a set of data analysis tools fo...
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08/29/2021
Survival Analysis with Graph-Based Regularization for Predictors
We study the variable selection problem in survival analysis to identify...
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05/31/2021
Early Detection of COVID-19 Hotspots Using Spatio-Temporal Data
Recently, the Centers for Disease Control and Prevention (CDC) has worke...
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05/29/2021
Robust Hypothesis Testing with Wasserstein Uncertainty Sets
We consider a data-driven robust hypothesis test where the optimal test ...
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04/09/2021
Sequential (Quickest) Change Detection: Classical Results and New Directions
Online detection of changes in stochastic systems, referred to as sequen...
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02/11/2021
Optimality of Graph Scanning Statistic for Online Community Detection
Sequential change-point detection for graphs is a fundamental problem fo...
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02/10/2021
Sequential change-point detection for mutually exciting point processes over networks
We present a new CUSUM procedure for sequentially detecting change-point...
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10/21/2020
Sequential Change Detection by Optimal Weighted ℓ_2 Divergence
We present a new non-parametric statistics, called the weighted ℓ_2 dive...
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09/15/2020
High-resolution Spatio-temporal Model for County-level COVID-19 Activity in the U.S
We present an interpretable high-resolution spatio-temporal model to est...
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06/12/2020
Uncertainty Quantification for Inferring Hawkes Networks
Multivariate Hawkes processes are commonly used to model streaming netwo...
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06/07/2020
Distributionally Robust k-Nearest Neighbors for Few-Shot Learning
Learning a robust classifier from a few samples remains a key challenge ...
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03/29/2020
Convex Recovery of Marked Spatio-Temporal Point Processes
We present a multi-dimensional Bernoulli process model for spatial-tempo...
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03/29/2020
Convex Parameter Recovery for Interacting Marked Processes
We introduce a new general modeling approach for multivariate discrete e...
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10/20/2019
Online Community Detection by Spectral CUSUM
We present an online community change detection algorithm called spectra...
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01/24/2019
Asynchronous Multi-Sensor Change-Point Detection for Seismic Tremors
We consider the sequential change-point detection for asynchronous multi...
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11/09/2018
Sequential Subspace Changepoint Detection
We consider the sequential changepoint detection problem of detecting ch...
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06/28/2018
First-order optimal sequential subspace change-point detection
We consider the sequential change-point detection problem of detecting c...
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05/27/2018
Robust Hypothesis Testing Using Wasserstein Uncertainty Sets
We develop a novel computationally efficient and general framework for r...
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06/15/2017