289 citations · 1.2k across the 72 of their papers we have counts for
6 papers · 1 filter
Performance Bounds for Expander-based Compressed Sensing in the presence of Poisson Noise
Sina Jafarpour, Rebecca Willett, Maxim Raginsky +1
This paper provides performance bounds for compressed sensing in the presence of Poisson noise using expander graphs. The Poisson noise model is appropriate for a variety of applic…
Sequential anomaly detection in the presence of noise and limited feedback
Maxim Raginsky, Rebecca Willett, Corinne Horn +2
This paper describes a methodology for detecting anomalies from sequentially observed and potentially noisy data. The proposed approach consists of two main elements: (1) {\em filt…
Compressed sensing performance bounds under Poisson noise
Maxim Raginsky, Rebecca M. Willett, Zachary T. Harmany +1
This paper describes performance bounds for compressed sensing (CS) where the underlying sparse or compressible (sparsely approximable) signal is a vector of nonnegative intensitie…
Sparse Poisson Intensity Reconstruction Algorithms
Zachary T. Harmany, Roummel F. Marcia, Rebecca M. Willett
The observations in many applications consist of counts of discrete events, such as photons hitting a dector, which cannot be effectively modeled using an additive bounded or Gauss…
The False Discovery Rate for Statistical Pattern Recognition
Clayton Scott, Gowtham Bellala, Rebecca Willett
The false discovery rate (FDR) and false nondiscovery rate (FNDR) have received considerable attention in the literature on multiple testing. These performance measures are also ap…
Performance bounds on compressed sensing with Poisson noise
Rebecca M. Willett, Maxim Raginsky
This paper describes performance bounds for compressed sensing in the presence of Poisson noise when the underlying signal, a vector of Poisson intensities, is sparse or compressib…