
Controlling the False Split Rate in TreeBased Aggregation
In many domains, data measurements can naturally be associated with the ...
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Fundamental Tradeoffs in Distributionally Adversarial Training
Adversarial training is among the most effective techniques to improve t...
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NearOptimal Model Discrimination with NonDisclosure
Let θ_0,θ_1 ∈ℝ^d be the population risk minimizers associated to some lo...
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Precise Statistical Analysis of Classification Accuracies for Adversarial Training
Despite the wide empirical success of modern machine learning algorithms...
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Dynamic Incentiveaware Learning: Robust Pricing in Contextual Auctions
Motivated by pricing in ad exchange markets, we consider the problem of ...
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Precise Tradeoffs in Adversarial Training for Linear Regression
Despite breakthrough performance, modern learning models are known to be...
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Online Debiasing for Adaptively Collected Highdimensional Data
Adaptive collection of data is increasingly commonplace in many applicat...
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New Computational and Statistical Aspects of Regularized Regression with Application to Rare Feature Selection and Aggregation
Prior knowledge on properties of a target model often come as discrete o...
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Analysis of a TwoLayer Neural Network via Displacement Convexity
Fitting a function by using linear combinations of a large number N of `...
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MultiProduct Dynamic Pricing in HighDimensions with Heterogenous Price Sensitivity
We consider the problem of multiproduct dynamic pricing in a contextual...
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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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False Discovery Rate Control via Debiased Lasso
We consider the problem of variable selection in highdimensional statis...
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Theoretical insights into the optimization landscape of overparameterized shallow neural networks
In this paper we study the problem of learning a shallow artificial neur...
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A Flexible Framework for Hypothesis Testing in Highdimensions
Hypothesis testing in the linear regression model is a fundamental stati...
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Perishability of Data: Dynamic Pricing under VaryingCoefficient Models
We consider a firm that sells a large number of products to its customer...
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Dynamic Pricing in Highdimensions
We study the pricing problem faced by a firm that sells a large number o...
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Performance of a community detection algorithm based on semidefinite programming
The problem of detecting communities in a graph is maybe one the most st...
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Online Rules for Control of False Discovery Rate and False Discovery Exceedance
Multiple hypothesis testing is a core problem in statistical inference a...
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Debiasing the Lasso: Optimal Sample Size for Gaussian Designs
Performing statistical inference in highdimension is an outstanding cha...
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1Bit Matrix Completion under Exact LowRank Constraint
We consider the problem of noisy 1bit matrix completion under an exact ...
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Model Selection for HighDimensional Regression under the Generalized Irrepresentability Condition
In the highdimensional regression model a response variable is linearly...
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Efficient Reinforcement Learning for High Dimensional Linear Quadratic Systems
We study the problem of adaptive control of a high dimensional linear qu...
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Hypothesis Testing in HighDimensional Regression under the Gaussian Random Design Model: Asymptotic Theory
We consider linear regression in the highdimensional regime where the n...
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Learning Topic Models and Latent Bayesian Networks Under Expansion Constraints
Unsupervised estimation of latent variable models is a fundamental probl...
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