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Statistical Inference After Adaptive Sampling in Non-Markovian Environments


Feb 14, 2022
Kelly W Zhang, Lucas Janson, Susan A Murphy


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Rate-matching the regret lower-bound in the linear quadratic regulator with unknown dynamics


Feb 11, 2022
Feicheng Wang, Lucas Janson


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Using Machine Learning to Test Causal Hypotheses in Conjoint Analysis


Jan 20, 2022
Dae Woong Ham, Kosuke Imai, Lucas Janson


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A Simple and Efficient Sampling-based Algorithm for General Reachability Analysis


Dec 10, 2021
Thomas Lew, Lucas Janson, Riccardo Bonalli, Marco Pavone


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Tactile Grasp Refinement using Deep Reinforcement Learning and Analytic Grasp Stability Metrics


Sep 23, 2021
Alexander Koenig, Zixi Liu, Lucas Janson, Robert Howe

* paper currently under review, 7 pages, 10 figures, video: https://www.youtube.com/watch?v=9Bg8ZEAEOGI, code: https://github.com/axkoenig/grasp_refinement 

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Statistical Inference with M-Estimators on Adaptively Collected Data


May 28, 2021
Kelly W. Zhang, Lucas Janson, Susan A. Murphy


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Statistical Inference with M-Estimators on Bandit Data


Apr 29, 2021
Kelly W. Zhang, Lucas Janson, Susan A. Murphy


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Exact Asymptotics for Linear Quadratic Adaptive Control


Nov 02, 2020
Feicheng Wang, Lucas Janson


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Cross-validation Confidence Intervals for Test Error


Jul 24, 2020
Pierre Bayle, Alexandre Bayle, Lucas Janson, Lester Mackey

* 40 pages, 14 figures 

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Inference for Batched Bandits


Feb 08, 2020
Kelly W. Zhang, Lucas Janson, Susan A. Murphy


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Map-Predictive Motion Planning in Unknown Environments


Oct 17, 2019
Amine Elhafsi, Boris Ivanovic, Lucas Janson, Marco Pavone


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Revisiting the Asymptotic Optimality of RRT*


Sep 20, 2019
Kiril Solovey, Lucas Janson, Edward Schmerling, Emilio Frazzoli, Marco Pavone

* Submitted to ICRA2020 

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


Apr 16, 2018
Lucas Janson, Tommy Hu, Marco Pavone


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Risk-Constrained Reinforcement Learning with Percentile Risk Criteria


Apr 06, 2017
Yinlam Chow, Mohammad Ghavamzadeh, Lucas Janson, Marco Pavone

* arXiv admin note: substantial text overlap with arXiv:1406.3339 

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Deterministic Sampling-Based Motion Planning: Optimality, Complexity, and Performance


May 03, 2016
Lucas Janson, Brian Ichter, Marco Pavone


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Optimal Sampling-Based Motion Planning under Differential Constraints: the Drift Case with Linear Affine Dynamics


Oct 26, 2015
Edward Schmerling, Lucas Janson, Marco Pavone


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An Asymptotically-Optimal Sampling-Based Algorithm for Bi-directional Motion Planning


Jul 27, 2015
Joseph A. Starek, Javier V. Gomez, Edward Schmerling, Lucas Janson, Luis Moreno, Marco Pavone

* Accepted to the 2015 IEEE Intelligent Robotics and Systems Conference in Hamburg, Germany. This submission represents the long version of the conference manuscript, with additional proof details (Section IV) regarding the asymptotic optimality of the BFMT* algorithm 

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Monte Carlo Motion Planning for Robot Trajectory Optimization Under Uncertainty


May 29, 2015
Lucas Janson, Edward Schmerling, Marco Pavone


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Optimal Sampling-Based Motion Planning under Differential Constraints: the Driftless Case


Mar 02, 2015
Edward Schmerling, Lucas Janson, Marco Pavone


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Fast Marching Tree: a Fast Marching Sampling-Based Method for Optimal Motion Planning in Many Dimensions


Feb 06, 2015
Lucas Janson, Edward Schmerling, Ashley Clark, Marco Pavone


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