10 citations · 31 across the 12 of their papers we have counts for
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stat.ML2021★ 3 cited
Intrinsic Dimension Estimation Using Wasserstein Distances
Adam Block, Zeyu Jia, Yury Polyanskiy +1
It has long been thought that high-dimensional data encountered in many practical machine learning tasks have low-dimensional structure, i.e., the manifold hypothesis holds. A natu…
stat.ML2021★ 4 cited
Majorizing Measures, Sequential Complexities, and Online Learning
Adam Block, Yuval Dagan, Sasha Rakhlin
We introduce the technique of generic chaining and majorizing measures for controlling sequential Rademacher complexity. We relate majorizing measures to the notion of fractional c…