
Universal Inference Using the Split Likelihood Ratio Test
We propose a general method for constructing hypothesis tests and confid...
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Gaussian Mixture Clustering Using Relative Tests of Fit
We consider clustering based on significance tests for Gaussian Mixture ...
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Efficient Topological Layer based on Persistent Landscapes
We propose a novel topological layer for general deep learning models ba...
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Minimax Confidence Intervals for the Sliced Wasserstein Distance
The Wasserstein distance has risen in popularity in the statistics and m...
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Cautious Deep Learning
Most classifiers operate by selecting the maximum of an estimate of the ...
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L_1 Trend Filtering: A Modern Statistical Tool for TimeDomain Astronomy and Astronomical Spectroscopy
The problem of estimating a onedimensional signal possessing mixed degr...
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Trend Filtering – II. Denoising Astronomical Signals with Varying Degrees of Smoothness
Trend filtering—first introduced into the astronomical literature in Pap...
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Hypothesis Testing For Densities and HighDimensional Multinomials: Sharp Local Minimax Rates
We consider the goodnessoffit testing problem of distinguishing whethe...
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Least Ambiguous SetValued Classifiers with Bounded Error Levels
In most classification tasks there are observations that are ambiguous a...
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Finding Singular Features
We present a method for finding high density, lowdimensional structures...
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Statistical Inference for Cluster Trees
A cluster tree provides a highlyinterpretable summary of a density func...
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DistributionFree Predictive Inference For Regression
We develop a general framework for distributionfree predictive inferenc...
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Classification Accuracy as a Proxy for Two Sample Testing
When data analysts train a classifier and check if its accuracy is signi...
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Minimax Lower Bounds for Linear Independence Testing
Linear independence testing is a fundamental informationtheoretic and s...
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Statistical Analysis of Persistence Intensity Functions
Persistence diagrams are twodimensional plots that summarize the topolo...
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Adaptivity and ComputationStatistics Tradeoffs for Kernel and Distance based High Dimensional Two Sample Testing
Nonparametric two sample testing is a decision theoretic problem that in...
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Statistical Inference using the MorseSmale Complex
The MorseSmale complex of a function f decomposes the sample space into...
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Optimal Ridge Detection using Coverage Risk
We introduce the concept of coverage risk as an error measure for densit...
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An Analysis of Active Learning With Uniform Feature Noise
In active learning, the user sequentially chooses values for feature X a...
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Risk Bounds For Mode Clustering
Density mode clustering is a nonparametric clustering method. The cluste...
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Nonparametric modal regression
Modal regression estimates the local modes of the distribution of Y give...
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On the Highdimensional Power of Lineartime Kernel TwoSample Testing under Meandifference Alternatives
Nonparametric two sample testing deals with the question of consistently...
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Influence Functions for Machine Learning: Nonparametric Estimators for Entropies, Divergences and Mutual Informations
We propose and analyze estimators for statistical functionals of one or ...
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On Estimating L_2^2 Divergence
We give a comprehensive theoretical characterization of a nonparametric ...
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The functional meanshift algorithm for mode hunting and clustering in infinite dimensions
We introduce the functional meanshift algorithm, an iterative algorithm...
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Estimating the distribution of Galaxy Morphologies on a continuous space
The incredible variety of galaxy shapes cannot be summarized by human de...
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Nonparametric Estimation of Renyi Divergence and Friends
We consider nonparametric estimation of L_2, Renyiα and Tsallisα diver...
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Estimating Undirected Graphs Under Weak Assumptions
We consider the problem of providing nonparametric confidence guarantees...
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Tight Lower Bounds for Homology Inference
The homology groups of a manifold are important topological invariants t...
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Cluster Trees on Manifolds
In this paper we investigate the problem of estimating the cluster tree ...
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Minimax Theory for Highdimensional Gaussian Mixtures with Sparse Mean Separation
While several papers have investigated computationally and statistically...
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A Conformal Prediction Approach to Explore Functional Data
This paper applies conformal prediction techniques to compute simultaneo...
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DistributionFree Distribution Regression
`Distribution regression' refers to the situation where a response Y dep...
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Nonparametric ridge estimation
We study the problem of estimating the ridges of a density function. Rid...
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The Nonparanormal SKEPTIC
We propose a semiparametric approach, named nonparanormal skeptic, for e...
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Densitysensitive semisupervised inference
Semisupervised methods are techniques for using labeled data (X_1,Y_1),....
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Differential Privacy for Functions and Functional Data
Differential privacy is a framework for privately releasing summaries of...
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High Dimensional Semiparametric Gaussian Copula Graphical Models
In this paper, we propose a semiparametric approach, named nonparanormal...
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Sparse Nonparametric Graphical Models
We present some nonparametric methods for graphical modeling. In the dis...
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Minimax Rates for Homology Inference
Often, high dimensional data lie close to a lowdimensional submanifold ...
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Adaptive Semisupervised Inference
Semisupervised methods inevitably invoke some assumption that links the ...
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Manifold estimation and singular deconvolution under Hausdorff loss
We find lower and upper bounds for the risk of estimating a manifold in ...
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Stability of DensityBased Clustering
High density clusters can be characterized by the connected components o...
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Union Support Recovery in Multitask Learning
We sharply characterize the performance of different penalization scheme...
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Forest Density Estimation
We study graph estimation and density estimation in high dimensions, usi...
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Time Varying Undirected Graphs
Undirected graphs are often used to describe high dimensional distributi...
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Compressed Regression
Recent research has studied the role of sparsity in high dimensional reg...
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Highdimensional variable selection
This paper explores the following question: what kind of statistical gua...
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Hypothesis Testing for HighDimensional Multinomials: A Selective Review
The statistical analysis of discrete data has been the subject of extens...
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Robust Multivariate Nonparametric Tests via ProjectionPursuit
In this work, we generalize the Cramérvon Mises statistic via projectio...
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