30 citations · 63 across the 9 of their papers we have counts for
11 papers
Adaptive Selective Sampling for Online Prediction with Experts
Rui M. Castro, Fredrik Hellström, Tim van Erven
We consider online prediction of a binary sequence with expert advice. For this setting, we devise label-efficient forecasting algorithms, which use a selective sampling scheme tha…
Anomaly Detection for a Large Number of Streams: A Permutation-Based Higher Criticism Approach
Ivo V. Stoepker, Rui M. Castro, Ery Arias-Castro +1
Anomaly detection when observing a large number of data streams is essential in a variety of applications, ranging from epidemiological studies to monitoring of complex systems. Hi…
Are there needles in a moving haystack? Adaptive sensing for detection of dynamically evolving signals
Rui M. Castro, Ervin Tánczos
In this paper we investigate the problem of detecting dynamically evolving signals. We model the signal as an dimensional vector that is either zero or has non-zero compone…
Distribution-Free Detection of Structured Anomalies: Permutation and Rank-Based Scans
Ery Arias-Castro, Rui M. Castro, Ervin Tánczos +1
The scan statistic is by far the most popular method for anomaly detection, being popular in syndromic surveillance, signal and image processing, and target detection based on sens…
Adaptive Compressed Sensing for Support Recovery of Structured Sparse Sets
Rui M. Castro, Ervin Tánczos
This paper investigates the problem of recovering the support of structured signals via adaptive compressive sensing. We examine several classes of structured support sets, and cha…
Adaptive Sensing for Estimation of Structured Sparse Signals
Ervin Tánczos, Rui M. Castro
In many practical settings one can sequentially and adaptively guide the collection of future data, based on information extracted from data collected previously. These sequential…
Detection of Correlations with Adaptive Sensing
Rui M. Castro, Gabor Lugosi, Pierre-André Savalle
The problem of detecting correlations from samples of a high-dimensional Gaussian vector has recently received a lot of attention. In most existing work, detection procedures are p…
Joint Optimization and Variable Selection of High-dimensional Gaussian Processes
Bo Chen, Rui Castro, Andreas Krause
Maximizing high-dimensional, non-convex functions through noisy observations is a notoriously hard problem, but one that arises in many applications. In this paper, we tackle this…
Adaptive Sensing of Congested Spectrum Bands
Ali Tajer, Rui M. Castro, Xiaodong Wang
Cognitive radios process their sensed information collectively in order to opportunistically identify and access under-utilized spectrum segments (spectrum holes). Due to the trans…
Adaptive sensing performance lower bounds for sparse signal detection and support estimation
Rui M. Castro
This paper gives a precise characterization of the fundamental limits of adaptive sensing for diverse estimation and testing problems concerning sparse signals. We consider in part…
Distilled Sensing: Adaptive Sampling for Sparse Detection and Estimation
Jarvis Haupt, Rui Castro, Robert Nowak
Adaptive sampling results in dramatic improvements in the recovery of sparse signals in white Gaussian noise. A sequential adaptive sampling-and-refinement procedure called Distill…