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20172025
most citedLow-rank extended Kalman filtering for online learning of neural networks from streaming data

2 citations · 6 across the 18 of their papers we have counts for

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5 papers · 1 filter

stat.ML2025

Generalized Factor Neural Network Model for High-dimensional Regression

Zichuan Guo, Mihai Cucuringu, Alexander Y. Shestopaloff

We tackle the challenges of modeling high-dimensional data sets, particularly those with latent low-dimensional structures hidden within complex, non-linear, and noisy relationship…

stat.ML2024

A unifying framework for generalised Bayesian online learning in non-stationary environments

Gerardo Duran-Martin, Leandro Sánchez-Betancourt, Alexander Y. Shestopaloff +1

We propose a unifying framework for methods that perform probabilistic online learning in non-stationary environments. We call the framework BONE, which stands for generalised (B)a…

stat.ML2024★ 1 cited

Outlier-robust Kalman Filtering through Generalised Bayes

Gerardo Duran-Martin, Matias Altamirano, Alexander Y. Shestopaloff +5

We derive a novel, provably robust, and closed-form Bayesian update rule for online filtering in state-space models in the presence of outliers and misspecified measurement models.…

stat.ML2023★ 2 cited

Low-rank extended Kalman filtering for online learning of neural networks from streaming data

Peter G. Chang, Gerardo Durán-Martín, Alexander Y Shestopaloff +2

We propose an efficient online approximate Bayesian inference algorithm for estimating the parameters of a nonlinear function from a potentially non-stationary data stream. The met…

stat.ML2023

Robust Detection of Lead-Lag Relationships in Lagged Multi-Factor Models

Yichi Zhang, Mihai Cucuringu, Alexander Y. Shestopaloff +1

In multivariate time series systems, key insights can be obtained by discovering lead-lag relationships inherent in the data, which refer to the dependence between two time series…