We introduce a new estimator, the simultaneous multiscale change point estimator SMUCE,
for the change point problem in exponential family regression. An unknown step function is …

" Symmetry is a complexity-reducing concept [...]; seek it every-where."-Alan J. PerlisMany
natural and man-made objects exhibit significant symmetries or contain repeated …

We consider the problem of detecting whether or not, in a given sensor network, there is a
cluster of sensors which exhibit an" unusual behavior." Formally, suppose we are given a set …

This paper considers the problem of detecting nonstationary phenomena, and chirps in
particular, from very noisy data. Chirps are waveforms of the very general form A (t) exp (ıλφ …

We review the ideas, algorithms, and numerical performance of manifold-based machine
learning and dimension reduction methods. The representative methods include locally …

Many real-world data sets can be viewed of as noisy samples of special types of metric
spaces called metric graphs [16]. Building on the notions of correspondence and Gromov …

Consider a graph with a set of vertices and oriented edges connecting pairs of vertices.
Each vertex is associated with a random variable and these are assumed to be …

Motivated by a broad range of potential applications in topological and geometric inference,
we introduce a weighted version of the k-nearest neighbor density estimate. Various …

Consider a large number of detectors each generating a data stream. The task is to detect
online, distribution changes in a small fraction of the data streams. Previous approaches to …

We consider the problem of identifying a sparse set of relevant columns and rows in a large
data matrix with highly corrupted entries. This problem of identifying groups from a collection …