
Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control
We introduce Learn then Test, a framework for calibrating machine learni...
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DoubleRobust TwoWayFixedEffects Regression For Panel Data
We propose a new estimator for the average causal effects of a binary tr...
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BONuS: Multiple multivariate testing with a dataadaptivetest statistic
We propose a new adaptive empirical Bayes framework, the BagOfNullSta...
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Testing for Outliers with Conformal pvalues
This paper studies the construction of pvalues for nonparametric outlie...
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Conformalized Survival Analysis
Existing survival analysis techniques heavily rely on strong modelling a...
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DistributionFree, RiskControlling Prediction Sets
While improving prediction accuracy has been the focus of machine learni...
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Conditional calibration for false discovery rate control under dependence
We introduce a new class of methods for finitesample false discovery ra...
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Conformal Inference of Counterfactuals and Individual Treatment Effects
Evaluating treatment effect heterogeneity widely informs treatment decis...
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Consistency of Spectral Clustering on Hierarchical Stochastic Block Models
We propose a generic network model, based on the Stochastic Block Model,...
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Adaptivity of Stochastic Gradient Methods for Nonconvex Optimization
Adaptivity is an important yet understudied property in modern optimiza...
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Variance Reduction with Sparse Gradients
Variance reduction methods such as SVRG and SpiderBoost use a mixture of...
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Smoothed Nested Testing on Directed Acyclic Graphs
We consider the problem of multiple hypothesis testing when there is a l...
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Unified ℓ_2→∞ Eigenspace Perturbation Theory for Symmetric Random Matrices
Modern applications in statistics, computer science and network science ...
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An AssumptionFree Exact Test For FixedDesign Linear Models With Exchangeable Errors
We propose the cyclic permutation test (CPT) to test general linear hypo...
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On the Adaptivity of Stochastic GradientBased Optimization
Stochasticgradientbased optimization has been a core enabling methodol...
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Regression adjustment in randomized experiments with a diverging number of covariates
Extending R. A. Fisher and D. A. Freedman's results on the analysis of c...
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Overlap in Observational Studies with HighDimensional Covariates
Causal inference in observational settings typically rests on a pair of ...
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Less than a Single Pass: Stochastically Controlled Stochastic Gradient Method
We develop and analyze a procedure for gradientbased optimization that ...
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Lihua Lei
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