41 citations · 143 across the 39 of their papers we have counts for
5 papers · 1 filter
Approximation and Estimation for High-Dimensional Deep Learning Networks
Andrew R. Barron, Jason M. Klusowski
It has been experimentally observed in recent years that multi-layer artificial neural networks have a surprising ability to generalize, even when trained with far more parameters…
Sharp Analysis of a Simple Model for Random Forests
Jason M. Klusowski
Random forests have become an important tool for improving accuracy in regression and classification problems since their inception by Leo Breiman in 2001. In this paper, we revisi…
Estimation of convex supports from noisy measurements
Victor-Emmanuel Brunel, Jason M. Klusowski, Dana Yang
A popular class of problem in statistics deals with estimating the support of a density from observations drawn at random from a -dimensional distribution. The one-dimension…
Counting Motifs with Graph Sampling
Jason M. Klusowski, Yihong Wu
Applied researchers often construct a network from a random sample of nodes in order to infer properties of the parent network. Two of the most widely used sampling schemes are sub…
Estimating the Number of Connected Components in a Graph via Subgraph Sampling
Jason M. Klusowski, Yihong Wu
Learning properties of large graphs from samples has been an important problem in statistical network analysis since the early work of Goodman \cite{Goodman1949} and Frank \cite{Fr…