602 citations · 2k across the 59 of their papers we have counts for
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Kernel Mean Estimation via Spectral Filtering
Krikamol Muandet, Bharath Sriperumbudur, Bernhard Schölkopf
The problem of estimating the kernel mean in a reproducing kernel Hilbert space (RKHS) is central to kernel methods in that it is used by classical approaches (e.g., when centering…
Learning Theory for Distribution Regression
Zoltan Szabo, Bharath Sriperumbudur, Barnabas Poczos +1
We focus on the distribution regression problem: regressing to vector-valued outputs from probability measures. Many important machine learning and statistical tasks fit into this…
Kernel Mean Shrinkage Estimators
Krikamol Muandet, Bharath Sriperumbudur, Kenji Fukumizu +2
A mean function in a reproducing kernel Hilbert space (RKHS), or a kernel mean, is central to kernel methods in that it is used by many classical algorithms such as kernel principa…
Two-stage Sampled Learning Theory on Distributions
Zoltan Szabo, Arthur Gretton, Barnabas Poczos +1
We focus on the distribution regression problem: regressing to a real-valued response from a probability distribution. Although there exist a large number of similarity measures be…