5 papers
Minimax optimal testing by classification
Patrik Róbert Gerber, Yanjun Han, Yury Polyanskiy
This paper considers an ML inspired approach to hypothesis testing known as classifier/classification-accuracy testing (). In , one first trains a class…
Optimal Quantization for Matrix Multiplication
Or Ordentlich, Yury Polyanskiy
Recent work in machine learning community proposed multiple methods for performing lossy compression (quantization) of large matrices. This quantization is important for accelerati…
Optimal empirical Bayes estimation for the Poisson model via minimum-distance methods
Soham Jana, Yury Polyanskiy, Yihong Wu
The Robbins estimator is the most iconic and widely used procedure in the empirical Bayes literature for the Poisson model. On one hand, this method has been recently shown to be m…
Density estimation using the perceptron
Patrik Róbert Gerber, Tianze Jiang, Yury Polyanskiy +1
We propose a new density estimation algorithm. Given i.i.d. observations from a distribution belonging to a class of densities on , our estimator outputs any dens…
Rate of convergence of the smoothed empirical Wasserstein distance
Adam Block, Zeyu Jia, Yury Polyanskiy +1
Consider an empirical measure induced by iid samples from a -dimensional -subgaussian distribution and let be the isotropi…