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05/25/2023
Exponential Smoothing for Off-Policy Learning
Off-policy learning (OPL) aims at finding improved policies from logged ...
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05/05/2023
Geodesically convex M-estimation in metric spaces
We study the asymptotic properties of geodesically convex M-estimation o...
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03/02/2023
Concentration of empirical barycenters in metric spaces
Barycenters (aka Fréchet means) were introduced in statistics in the 194...
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10/19/2020
Statistical guarantees for generative models without domination
In this paper, we introduce a convenient framework for studying (adversa...
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06/17/2020
Scalable Learning and MAP Inference for Nonsymmetric Determinantal Point Processes
Determinantal point processes (DPPs) have attracted significant attentio...
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02/19/2020
Propose, Test, Release: Differentially private estimation with high probability
We derive concentration inequalities for differentially private median a...
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06/27/2019
Differentially private sub-Gaussian location estimators
We tackle the problem of estimating a location parameter with differenti...
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05/30/2019
Learning Nonsymmetric Determinantal Point Processes
Determinantal point processes (DPPs) have attracted substantial attentio...
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03/15/2019
A nonasymptotic law of iterated logarithm for robust online estimators
In this paper, we provide tight deviation bounds for M-estimators, which...
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02/28/2019
Learning rates for Gaussian mixtures under group invariance
We study the pointwise maximum likelihood estimation rates for a class o...
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11/01/2018
Learning Signed Determinantal Point Processes through the Principal Minor Assignment Problem
Symmetric determinantal point processes (DPP's) are a class of probabili...
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09/05/2018
A change-point problem and inference for segment signals
We address the problem of detection and estimation of one or two change-...
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04/26/2018
Estimation of convex supports from noisy measurements
A popular class of problem in statistics deals with estimating the suppo...
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02/26/2018