129 citations · 568 across the 49 of their papers we have counts for
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Reliable Semi-Supervised Learning when Labels are Missing at Random
Xiuming Liu, Dave Zachariah, Johan Wågberg +1
Semi-supervised learning methods are motivated by the availability of large datasets with unlabeled features in addition to labeled data. Unlabeled data is, however, not guaranteed…
From to : a finer analysis of perturbed branching Brownian motion
Anton Bovier, Lisa Hartung
The logarithmic correction for the order of the maximum for two-speed branching Brownian motion changes discontinuously when approaching slopes which corresponds to…
Learning Localized Spatio-Temporal Models From Streaming Data
Muhammad Osama, Dave Zachariah, Thomas B. Schön
We address the problem of predicting spatio-temporal processes with temporal patterns that vary across spatial regions, when data is obtained as a stream. That is, when the trainin…
Composite Gaussian Processes: Scalable Computation and Performance Analysis
Xiuming Liu, Dave Zachariah, Edith C. H. Ngai
Gaussian process (GP) models provide a powerful tool for prediction but are computationally prohibitive using large data sets. In such scenarios, one has to resort to approximate m…