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Near-optimal detection of geometric objects by fast multiscale methods
We construct detectors for "geometric" objects in noisy data. Examples include a detector for presence of a line segment of unknown length, position, and orientation in two-dimensional image dataExpand
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Large-Scale Absence of Sharks on Reefs in the Greater-Caribbean: A Footprint of Human Pressures
Background In recent decades, large pelagic and coastal shark populations have declined dramatically with increased fishing; however, the status of sharks in other systems such as coral reefs remainsExpand
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On the Estimation of the Gradient Lines of a Density and the Consistency of the Mean-Shift Algorithm
TLDR
We consider the problem of estimating the gradient lines of a density, which can be used to cluster points sampled from that density, for example via the mean-shift algorithm of Fukunaga and Hostetler. Expand
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Spectral Clustering Based on Local PCA
TLDR
We propose a spectral clustering method based on local principal components analysis (PCA). Expand
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On the Fundamental Limits of Adaptive Sensing
TLDR
We prove that the advantages offered by clever adaptive strategies and sophisticated estimation procedures-no matter how intractable-over classical compressed acquisition/recovery schemes are minimal. Expand
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Community Detection in Random Networks
We formalize the problem of detecting a community in a network into testing whether in a given (random) graph there is a subgraph that is unusually dense. We observe an undirected and unweightedExpand
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Compressive binary search
TLDR
In this paper we consider the problem of locating a nonzero entry in a high-dimensional vector from possibly adaptive linear measurements. Expand
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Detecting Positive Correlations in a Multivariate Sample
We consider the problem of testing whether a correlation matrix of a multivariate normal population is the identity matrix. We focus on sparse classes of alternatives where only a few entries areExpand
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Cluster detection in networks using percolation
We consider the task of detecting a salient cluster in a sensor network, that is, an undirected graph with a random variable attached to each node. Motivated by recent research in environmentalExpand
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