
An Adaptive Strategy for Active Learning with Smooth Decision Boundary
We present the first adaptive strategy for active learning in the settin...
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Twosample Hypothesis Testing for Inhomogeneous Random Graphs
The study of networks leads to a wide range of high dimensional inferenc...
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TwoSample Tests for Large Random Graphs Using Network Statistics
We consider a twosample hypothesis testing problem, where the distribut...
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Adaptivity to Noise Parameters in Nonparametric Active Learning
This work addresses various open questions in the theory of active learn...
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Tight (Lower) Bounds for the Fixed Budget Best Arm Identification Bandit Problem
We consider the problem of best arm identification with a fixed budget T...
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An optimal algorithm for the Thresholding Bandit Problem
We study a specific combinatorial pure exploration stochastic bandit pro...
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Learning relationships between data obtained independently
The aim of this paper is to provide a new method for learning the relati...
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Simple regret for infinitely many armed bandits
We consider a stochastic bandit problem with infinitely many arms. In th...
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Implementable confidence sets in high dimensional regression
We consider the setting of linear regression in high dimension. We focus...
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Toward Optimal Stratification for Stratified MonteCarlo Integration
We consider the problem of adaptive stratified sampling for Monte Carlo ...
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Adaptive Stratified Sampling for MonteCarlo integration of Differentiable functions
We consider the problem of adaptive stratified sampling for Monte Carlo ...
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Minimax rate of testing in sparse linear regression
We consider the problem of testing the hypothesis that the parameter of ...
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Contextual Bandits under Delayed Feedback
Delayed feedback is an ubiquitous problem in many industrial systems emp...
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A minimax nearoptimal algorithm for adaptive rejection sampling
Rejection Sampling is a fundamental MonteCarlo method. It is used to sa...
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Total variation distance for discretely observed Lévy processes: a Gaussian approximation of the small jumps
It is common practice to treat small jumps of Lévy processes as Wiener n...
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Rotting bandits are no harder than stochastic ones
In bandits, arms' distributions are stationary. This is often violated i...
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Estimating minimum effect with outlier selection
We introduce onesided versions of Huber's contamination model, in which...
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Optimal Sparsity Testing in Linear regression Model
We consider the problem of sparsity testing in the highdimensional line...
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Local minimax rates for closeness testing of discrete distributions
We consider the closeness testing (or twosample testing) problem in the...
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Restless dependent bandits with fading memory
We study the stochastic multiarmed bandit problem in the case when the ...
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Alexandra Carpentier
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Chair of Mathematical Statistics and Machine Learning in the Institute of Mathematical Stochastics (IMST) , Faculty of Mathematics (FMA) , Otto von Guericke University Magdeburg .