Lucas Janson

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Harvard University ∙ Stanford University

Powerful Knockoffs via Minimizing Reconstructability

Model-X knockoffs allows analysts to perform feature selection using alm...
11/30/2020 ∙ by Asher Spector, et al. ∙ 0 ∙ share

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Exact Asymptotics for Linear Quadratic Adaptive Control

Recent progress in reinforcement learning has led to remarkable performa...
11/02/2020 ∙ by Feicheng Wang, et al. ∙ 0 ∙ share

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A Power Analysis of the Conditional Randomization Test and Knockoffs

In many scientific problems, researchers try to relate a response variab...
10/05/2020 ∙ by Wenshuo Wang, et al. ∙ 0 ∙ share

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Cross-validation Confidence Intervals for Test Error

This work develops central limit theorems for cross-validation and consi...
07/24/2020 ∙ by Pierre Bayle, et al. ∙ 0 ∙ share

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Testing goodness-of-fit and conditional independence with approximate co-sufficient sampling

Goodness-of-fit (GoF) testing is ubiquitous in statistics, with direct t...
07/20/2020 ∙ by Rina Foygel Barber, et al. ∙ 0 ∙ share

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Floodgate: inference for model-free variable importance

Many modern applications seek to understand the relationship between an ...
07/02/2020 ∙ by Lu Zhang, et al. ∙ 0 ∙ share

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Fast and Powerful Conditional Randomization Testing via Distillation

In relating a response variable Y to covariates (Z,X), a key question is...
06/06/2020 ∙ by Molei Liu, et al. ∙ 0 ∙ share

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Inference for Batched Bandits

As bandit algorithms are increasingly utilized in scientific studies, th...
02/08/2020 ∙ by Kelly W. Zhang, et al. ∙ 14 ∙ share

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Map-Predictive Motion Planning in Unknown Environments

Algorithms for motion planning in unknown environments are generally lim...
10/17/2019 ∙ by Amine Elhafsi, et al. ∙ 0 ∙ share

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Revisiting the Asymptotic Optimality of RRT*

RRT* is one of the most widely used sampling-based algorithms for asympt...
09/20/2019 ∙ by Kiril Solovey, et al. ∙ 0 ∙ share

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Relaxing the Assumptions of Knockoffs by Conditioning

The recent paper Candès et al. (2018) introduced model-X knockoffs, a me...
03/07/2019 ∙ by Dongming Huang, et al. ∙ 0 ∙ share

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Metropolized Knockoff Sampling

Model-X knockoffs is a wrapper that transforms essentially any feature i...
03/01/2019 ∙ by Stephen Bates, et al. ∙ 0 ∙ share

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Safe Motion Planning in Unknown Environments: Optimality Benchmarks and Tractable Policies

This paper addresses the problem of planning a safe (i.e., collision-fre...
04/16/2018 ∙ by Lucas Janson, et al. ∙ 0 ∙ share

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Risk-Constrained Reinforcement Learning with Percentile Risk Criteria

In many sequential decision-making problems one is interested in minimiz...
12/05/2015 ∙ by Yinlam Chow, et al. ∙ 0 ∙ share

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Lucas Janson

Featured Co-authors

Marco Pavone

Lu Zhang

Mohammad Ghavamzadeh

Lester Mackey

Wenshuo Wang

Yinlam Chow

Emilio Frazzoli

Rina Foygel Barber

Kiril Solovey

Boris Ivanovic

Susan A. Murphy

Powerful Knockoffs via Minimizing Reconstructability

Exact Asymptotics for Linear Quadratic Adaptive Control

A Power Analysis of the Conditional Randomization Test and Knockoffs

Cross-validation Confidence Intervals for Test Error

Testing goodness-of-fit and conditional independence with approximate co-sufficient sampling

Floodgate: inference for model-free variable importance

Fast and Powerful Conditional Randomization Testing via Distillation

Inference for Batched Bandits

Map-Predictive Motion Planning in Unknown Environments

Revisiting the Asymptotic Optimality of RRT*

Relaxing the Assumptions of Knockoffs by Conditioning

Metropolized Knockoff Sampling

Safe Motion Planning in Unknown Environments: Optimality Benchmarks and Tractable Policies

Risk-Constrained Reinforcement Learning with Percentile Risk Criteria