7 papers
Mixture and separation of log-concave measures
March T. Boedihardjo, Yao Xie
For a two-component log-concave mixture model, we investigate the extent to which the weight, mean, and covariance of each component distribution can be accurately recovered when g…
Testing the mixture model hypothesis via spectral gap
March T. Boedihardjo, Joe Kileel, Vandy Tombs
In this paper, we study the problem of testing whether or not a given probability measure on can be decomposed as a mixture of two probability measures whose…
Optimality of empirical measures as quantizers
March T. Boedihardjo
A common way to discretize a probability measure is to use an empirical measure as a discrete approximation. But how far from being optimal is this approximation in the p-Wasserste…
Statistical and Computational Guarantees of Kernel Max-Sliced Wasserstein Distances
Jie Wang, March Boedihardjo, Yao Xie
Optimal transport has been very successful for various machine learning tasks; however, it is known to suffer from the curse of dimensionality. Hence, dimensionality reduction is d…
On Extended Concentration Inequalities for Fast JL Embeddings of Infinite Sets
Edem Boahen, March T. Boedihardjo, Rafael Chiclana +1
The Johnson-Lindenstrauss (JL) lemma allows subsets of a high-dimensional space to be embedded into a lower-dimensional space while approximately preserving all pairwise Euclidean…
Injective norm of random tensors with independent entries
March T. Boedihardjo
We obtain a non-asymptotic bound for the expected injective norm of a random tensor with independent entries. This bound is similar to the bound by Bandeira and van Handel (2016) f…