Search Results for author: Yajun Mei

Found 11 papers, 0 papers with code

Covariance Estimators for the ROOT-SGD Algorithm in Online Learning

no code implementations2 Dec 2022 Yiling Luo, Xiaoming Huo, Yajun Mei

Our second estimator is a Hessian-free estimator that overcomes the aforementioned limitation.

Adaptive Partially-Observed Sequential Change Detection and Isolation

no code implementations9 Aug 2022 Xinyu Zhao, Jiuyun Hu, Yajun Mei, Hao Yan

High-dimensional data has become popular due to the easy accessibility of sensors in modern industrial applications.

Change Detection Change Point Detection

Adaptive Resources Allocation CUSUM for Binomial Count Data Monitoring with Application to COVID-19 Hotspot Detection

no code implementations9 Aug 2022 Jiuyun Hu, Yajun Mei, Sarah Holte, Hao Yan

In this paper, we present an efficient statistical method (denoted as "Adaptive Resources Allocation CUSUM") to robustly and efficiently detect the hotspot with limited sampling resources.

Change Point Detection

Implicit Regularization Properties of Variance Reduced Stochastic Mirror Descent

no code implementations29 Apr 2022 Yiling Luo, Xiaoming Huo, Yajun Mei

On the other hand, algorithms such as gradient descent and stochastic gradient descent have the implicit regularization property that leads to better performance in terms of the generalization errors.

The Directional Bias Helps Stochastic Gradient Descent to Generalize in Kernel Regression Models

no code implementations29 Apr 2022 Yiling Luo, Xiaoming Huo, Yajun Mei

In addition, the Gradient Descent (GD) with a moderate or small step-size converges along the direction that corresponds to the smallest eigenvalue.


Private Sequential Hypothesis Testing for Statisticians: Privacy, Error Rates, and Sample Size

no code implementations10 Apr 2022 Wanrong Zhang, Yajun Mei, Rachel Cummings

We also empirically validate our theoretical results on several synthetic databases, showing that our algorithms also perform well in practice.

Active Learning-Based Multistage Sequential Decision-Making Model with Application on Common Bile Duct Stone Evaluation

no code implementations13 Jan 2022 Hongzhen Tian, Reuven Zev Cohen, Chuck Zhang, Yajun Mei

For both simulation and testing cohorts, the proposed method is more effective, stable, interpretable, and computationally efficient on parameter estimation.

Active Learning Decision Making

Directional Bias Helps Stochastic Gradient Descent to Generalize in Nonparametric Model

no code implementations29 Sep 2021 Yiling Luo, Xiaoming Huo, Yajun Mei

This paper studies the Stochastic Gradient Descent (SGD) algorithm in kernel regression.


Asymptotic Theory of $\ell_1$-Regularized PDE Identification from a Single Noisy Trajectory

no code implementations12 Mar 2021 Yuchen He, Namjoon Suh, Xiaoming Huo, Sungha Kang, Yajun Mei

We provide a set of sufficient conditions which guarantee that, from a single trajectory data denoised by a Local-Polynomial filter, the support of $\mathbf{c}(\lambda)$ asymptotically converges to the true signed-support associated with the underlying PDE for sufficiently many data and a certain range of $\lambda$.

Bandit Change-Point Detection for Real-Time Monitoring High-Dimensional Data Under Sampling Control

no code implementations24 Sep 2020 Wanrong Zhang, Yajun Mei

In many real-world problems of real-time monitoring high-dimensional streaming data, one wants to detect an undesired event or change quickly once it occurs, but under the sampling control constraint in the sense that one might be able to only observe or use selected components data for decision-making per time step in the resource-constrained environments.

Change Point Detection Decision Making +1

Differentially Private Change-Point Detection

no code implementations NeurIPS 2018 Rachel Cummings, Sara Krehbiel, Yajun Mei, Rui Tuo, Wanrong Zhang

The change-point detection problem seeks to identify distributional changes at an unknown change-point k* in a stream of data.

Change Point Detection Fault Detection

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