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09/07/2023
Total Variation Floodgate for Variable Importance Inference in Classification
Inferring variable importance is the key problem of many scientific stud...
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02/27/2023
Estimating the Convex Hull of the Image of a Set with Smooth Boundary: Error Bounds and Applications
We study the problem of estimating the convex hull of the image f(X)⊂ℝ^n...
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01/13/2023
Randomization Tests for Adaptively Collected Data
Randomization testing is a fundamental method in statistics, enabling in...
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12/21/2022
Powerful Partial Conjunction Hypothesis Testing via Conditioning
Research questions across a diverse array of fields are formulated as a ...
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08/11/2022
Surrogate-based global sensitivity analysis with statistical guarantees via floodgate
Computational models are utilized in many scientific domains to simulate...
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03/31/2022
Controlled Discovery and Localization of Signals via Bayesian Linear Programming
Scientists often must simultaneously discover signals and localize them ...
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02/14/2022
Statistical Inference After Adaptive Sampling in Non-Markovian Environments
There is a great desire to use adaptive sampling methods, such as reinfo...
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02/11/2022
Rate-matching the regret lower-bound in the linear quadratic regulator with unknown dynamics
The theory of reinforcement learning currently suffers from a mismatch b...
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01/20/2022
Using Machine Learning to Test Causal Hypotheses in Conjoint Analysis
Conjoint analysis is a popular experimental design used to measure multi...
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12/10/2021
A Simple and Efficient Sampling-based Algorithm for General Reachability Analysis
In this work, we analyze an efficient sampling-based algorithm for gener...
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09/23/2021
Tactile Grasp Refinement using Deep Reinforcement Learning and Analytic Grasp Stability Metrics
Reward functions are at the heart of every reinforcement learning (RL) a...
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04/29/2021
Statistical Inference with M-Estimators on Bandit Data
Bandit algorithms are increasingly used in real world sequential decisio...
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11/30/2020
Powerful Knockoffs via Minimizing Reconstructability
Model-X knockoffs allows analysts to perform feature selection using alm...
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11/02/2020
Exact Asymptotics for Linear Quadratic Adaptive Control
Recent progress in reinforcement learning has led to remarkable performa...
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10/05/2020
A Power Analysis of the Conditional Randomization Test and Knockoffs
In many scientific problems, researchers try to relate a response variab...
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07/24/2020
Cross-validation Confidence Intervals for Test Error
This work develops central limit theorems for cross-validation and consi...
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07/20/2020
Testing goodness-of-fit and conditional independence with approximate co-sufficient sampling
Goodness-of-fit (GoF) testing is ubiquitous in statistics, with direct t...
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07/02/2020
Floodgate: inference for model-free variable importance
Many modern applications seek to understand the relationship between an ...
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06/06/2020
Fast and Powerful Conditional Randomization Testing via Distillation
In relating a response variable Y to covariates (Z,X), a key question is...
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02/08/2020
Inference for Batched Bandits
As bandit algorithms are increasingly utilized in scientific studies, th...
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10/17/2019
Map-Predictive Motion Planning in Unknown Environments
Algorithms for motion planning in unknown environments are generally lim...
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09/20/2019
Revisiting the Asymptotic Optimality of RRT*
RRT* is one of the most widely used sampling-based algorithms for asympt...
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03/07/2019
Relaxing the Assumptions of Knockoffs by Conditioning
The recent paper Candès et al. (2018) introduced model-X knockoffs, a me...
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03/01/2019
Metropolized Knockoff Sampling
Model-X knockoffs is a wrapper that transforms essentially any feature i...
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04/16/2018
Safe Motion Planning in Unknown Environments: Optimality Benchmarks and Tractable Policies
This paper addresses the problem of planning a safe (i.e., collision-fre...
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12/05/2015