collaborators

8 papers

stat.ME2026

Analytic Standard Errors for Latent Gaussian Discrete-Valued Multivariate Time Series

Christopher M. Crawford, Marie-Christine Düker, Younghoon Kim +3

Unlike their continuous-valued counterparts, there are no universally preferred methodologies for modeling discrete-valued time series. This is especially problematic in fields suc…

cs.LG2026

Consistency of Lloyd's Algorithm Under Perturbations

Dhruv Patel, Hui Shen, Shankar Bhamidi +2

In the context of unsupervised learning, Lloyd's algorithm is one of the most widely used clustering algorithms. It has inspired a plethora of work investigating the correctness of…

stat.ME2026

Testing common structure in high-dimensional factor models: change-point and two-sample procedures

Marie-Christine Düker, Vladas Pipiras

This work proposes a novel procedure to test for common structures across two high-dimensional factor models. The introduced test allows to uncover whether two factor models are dr…

stat.ME2026

Parametric multi-fidelity Monte Carlo estimation with applications to extremes

Minji Kim, Brendan Brown, Vladas Pipiras

In a multi-fidelity setting, data are available from two sources, high- and low-fidelity. Low-fidelity data has larger size and can be leveraged to make more efficient inference ab…

cs.NI2026

Confidence Driven Classification of Application Types in the Presence of Background Network Traffic

Eun Hun Choi, Jasleen Kaur, Vladas Pipiras +2

Accurately classifying the application types of network traffic using deep learning models has recently gained popularity. However, we find that these classifiers do not perform we…

math.PR2025

Attribute network models, stochastic approximation, and network sampling and ranking algorithms

Nelson Antunes, Sayan Banerjee, Shankar Bhamidi +1

We analyze dynamic random network models where younger vertices connect to older ones with probabilities proportional to their degrees as well as a propensity kernel governed by th…