— Sampling-based motion planners are often used to solve very high-dimensional planning problems. Many recent algorithms use projections of the state space to estimate properties...
The Johnson-Lindenstrauss random projection lemma gives a simple way to reduce the dimensionality of a set of points while approximately preserving their pairwise distances. The m...
In this paper, we consider a forensic multimodal authentication framework based on binary hypothesis testing in random projections domain. We formulate a generic authentication pr...
Random projection is a simple technique that has had a number of applications in algorithm design. In the context of machine learning, it can provide insight into questions such as...
Recent theoretical work has identified random projection as a promising dimensionality reduction technique for learning mixtures of Gaussians. Here we summarize these results and ...