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stat.ML2019★ 15 cited
Orthogonal Estimation of Wasserstein Distances
Mark Rowland, Jiri Hron, Yunhao Tang +3
Wasserstein distances are increasingly used in a wide variety of applications in machine learning. Sliced Wasserstein distances form an important subclass which may be estimated ef…
stat.ML2016
Fast nonlinear embeddings via structured matrices
Krzysztof Choromanski, Francois Fagan
We present a new paradigm for speeding up randomized computations of several frequently used functions in machine learning. In particular, our paradigm can be applied for improving…