1 citations · 2 across the 6 of their papers we have counts for
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stat.ML2025
Optimal Online Change Detection via Random Fourier Features
Florian Kalinke, Shakeel Gavioli-Akilagun
This article studies the problem of online non-parametric change point detection in multivariate data streams. We approach the problem through the lens of kernel-based two-sample t…
cs.LG2025★ 1 cited
Robust Partial-Label Learning by Leveraging Class Activation Values
Tobias Fuchs, Florian Kalinke
Real-world training data is often noisy; for example, human annotators assign conflicting class labels to the same instances. Partial-label learning (PLL) is a weakly supervised le…
cs.LG2025★ 1 cited
Partial-Label Learning with Conformal Candidate Cleaning
Tobias Fuchs, Florian Kalinke
Real-world data is often ambiguous; for example, human annotation produces instances with multiple conflicting class labels. Partial-label learning (PLL) aims at training a classif…