
Template Matching with Ranks
We consider the problem of matching a template to a noisy signal. Motiva...
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Minimax Estimation of Distances on a Surface and Minimax Manifold Learning in the IsometrictoConvex Setting
We start by considering the problem of estimating intrinsic distances on...
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On the Consistency of Metric and NonMetric Kmedoids
We establish the consistency of Kmedoids in the context of metric space...
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Template Matching and Change Point Detection by Mestimation
We consider the fundamental problem of matching a template to a signal. ...
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Anomaly Detection in Stationary Settings: A PermutationBased Higher Criticism Approach
Anomaly detection when observing a large number of data streams is essen...
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KMeans and Gaussian Mixture Modeling with a Separation Constraint
We consider the problem of clustering with Kmeans and Gaussian mixture ...
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A Multiscale Scan Statistic for Adaptive Submatrix Localization
We consider the problem of localizing a submatrix with largerthanusual...
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Detection of Sparse Positive Dependence
In a bivariate setting, we consider the problem of detecting a sparse co...
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Perturbation Bounds for Procrustes, Classical Scaling, and Trilateration, with Applications to Manifold Learning
One of the common tasks in unsupervised learning is dimensionality reduc...
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A Scan Procedure for Multiple Testing
In a multiple testing framework, we propose a method that identifies the...
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The Sparse Variance Contamination Model
We consider a Gaussian contamination (i.e., mixture) model where the con...
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On the Estimation of Latent Distances Using Graph Distances
We are given the adjacency matrix of a geometric graph and the task of r...
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Detection of Sparse Mixtures: Higher Criticism and Scan Statistic
We consider the problem of detecting a sparse mixture as studied by Ings...
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RANSAC Algorithms for Subspace Recovery and Subspace Clustering
We consider the RANSAC algorithm in the context of subspace recovery and...
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Unconstrained and CurvatureConstrained ShortestPath Distances and their Approximation
We study shortest paths and their distances on a subset of a Euclidean s...
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A Simple Approach to Sparse Clustering
Consider the problem of sparse clustering, where it is assumed that only...
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A Nonparametric Framework for Quantifying Generative Inference on Neuromorphic Systems
Restricted Boltzmann Machines and Deep Belief Networks have been success...
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Community Detection in Sparse Random Networks
We consider the problem of detecting a tight community in a sparse rando...
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Community Detection in Random Networks
We formalize the problem of detecting a community in a network into test...
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Spectral Clustering Based on Local PCA
We propose a spectral clustering method based on local principal compone...
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On the convergence of maximum variance unfolding
Maximum Variance Unfolding is one of the main methods for (nonlinear) di...
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A twostage denoising filter: the preprocessed Yaroslavsky filter
This paper describes a simple image noise removal method which combines ...
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Oracle inequalities and minimax rates for nonlocal means and related adaptive kernelbased methods
This paper describes a novel theoretical characterization of the perform...
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Spectral clustering based on local linear approximations
In the context of clustering, we assume a generative model where each cl...
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Clustering Based on Pairwise Distances When the Data is of Mixed Dimensions
In the context of clustering, we consider a generative model in a Euclid...
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Ery AriasCastro
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Professor in Department of Mathematics at University of California, San Diego