Lucas Janson

According to our database, Lucas Janson authored at least 31 papers between 2013 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Stronger Regret Bounds for Safe Online Reinforcement Learning in the Linear Quadratic Regulator.

Benjamin Schiffer, Lucas Janson

CoRR, 2024

SOAP: Improving and Stabilizing Shampoo using Adam.

Nikhil Vyas, Depen Morwani, Rosie Zhao, Itai Shapira, David Brandfonbrener, Lucas Janson, Sham M. Kakade

CoRR, 2024

Optimal ablation for interpretability.

Maximilian Li, Lucas Janson

CoRR, 2024

A New Perspective on Shampoo's Preconditioner.

Depen Morwani, Itai Shapira, Nikhil Vyas, Eran Malach, Sham M. Kakade, Lucas Janson

CoRR, 2024

Evaluating the Effectiveness of Index-Based Treatment Allocation.

Niclas Boehmer, Yash Nair, Sanket Shah, Lucas Janson, Aparna Taneja, Milind Tambe

CoRR, 2024

A Bayesian Approach to Online Learning for Contextual Restless Bandits with Applications to Public Health.

Biyonka Liang, Lily Xu, Aparna Taneja, Milind Tambe, Lucas Janson

CoRR, 2024

Total Variation Floodgate for Variable Importance Inference in Classification.

Wenshuo Wang, Lucas Janson, Lihua Lei, Aaditya Ramdas

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Estimating the convex hull of the image of a set with smooth boundary: error bounds and applications.

Thomas Lew, Riccardo Bonalli, Lucas Janson, Marco Pavone

CoRR, 2023

Rate-Matching the Regret Lower-Bound in the Linear Quadratic Regulator with Unknown Dynamics.

Feicheng Wang, Lucas Janson

Proceedings of the 62nd IEEE Conference on Decision and Control, 2023

2022

Statistical Inference After Adaptive Sampling in Non-Markovian Environments.

Kelly W. Zhang, Lucas Janson, Susan A. Murphy

CoRR, 2022

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

Thomas Lew, Lucas Janson, Riccardo Bonalli, Marco Pavone

Proceedings of the Learning for Dynamics and Control Conference, 2022

The Role of Tactile Sensing in Learning and Deploying Grasp Refinement Algorithms.

Alexander Koenig, Zixi Liu, Lucas Janson, Robert D. Howe

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

2021

A statistical model for describing and simulating microbial community profiles.

Siyuan Ma, Boyu Ren, Himel Mallick, Yo Sup Moon, Emma H. Schwager, Sagun Maharjan, Timothy L. Tickle, Yiren Lu, Rachel N. Carmody, Eric A. Franzosa, Lucas Janson, Curtis Huttenhower

PLoS Comput. Biol., 2021

Exact Asymptotics for Linear Quadratic Adaptive Control.

Feicheng Wang, Lucas Janson

J. Mach. Learn. Res., 2021

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

Alexander Koenig, Zixi Liu, Lucas Janson, Robert D. Howe

CoRR, 2021

Statistical Inference with M-Estimators on Bandit Data.

Kelly W. Zhang, Lucas Janson, Susan A. Murphy

CoRR, 2021

Statistical Inference with M-Estimators on Adaptively Collected Data.

Kelly W. Zhang, Lucas Janson, Susan A. Murphy

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Inference for Batched Bandits.

Kelly W. Zhang, Lucas Janson, Susan A. Murphy

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Cross-validation Confidence Intervals for Test Error.

Pierre Bayle, Alexandre Bayle, Lucas Janson, Lester Mackey

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Revisiting the Asymptotic Optimality of RRT.

Kiril Solovey, Lucas Janson, Edward Schmerling, Emilio Frazzoli, Marco Pavone

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

Map-Predictive Motion Planning in Unknown Environments.

Amine Elhafsi, Boris Ivanovic, Lucas Janson, Marco Pavone

Proceedings of the 2020 IEEE International Conference on Robotics and Automation, 2020

2018

Deterministic sampling-based motion planning: Optimality, complexity, and performance.

Lucas Janson, Brian Ichter, Marco Pavone

Int. J. Robotics Res., 2018

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

Lucas Janson, Tommy Hu, Marco Pavone

Proceedings of the Robotics: Science and Systems XIV, 2018

2017

Risk-Constrained Reinforcement Learning with Percentile Risk Criteria.

Yinlam Chow, Mohammad Ghavamzadeh, Lucas Janson, Marco Pavone

J. Mach. Learn. Res., 2017

2015

Fast marching tree: A fast marching sampling-based method for optimal motion planning in many dimensions.

Lucas Janson, Edward Schmerling, Ashley A. Clark, Marco Pavone

Int. J. Robotics Res., 2015

Monte Carlo Motion Planning for Robot Trajectory Optimization Under Uncertainty.

Lucas Janson, Edward Schmerling, Marco Pavone

Proceedings of the Robotics Research, 2015

An asymptotically-optimal sampling-based algorithm for Bi-directional motion planning.

Joseph A. Starek, Javier V. Gómez, Edward Schmerling, Lucas Janson, Luis Moreno, Marco Pavone

Proceedings of the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2015

Optimal sampling-based motion planning under differential constraints: The driftless case.

Edward Schmerling, Lucas Janson, Marco Pavone

Proceedings of the IEEE International Conference on Robotics and Automation, 2015

Optimal sampling-based motion planning under differential constraints: The drift case with linear affine dynamics.

Edward Schmerling, Lucas Janson, Marco Pavone

Proceedings of the 54th IEEE Conference on Decision and Control, 2015

2013

Fast Marching Trees: a Fast Marching Sampling-Based Method for Optimal Motion Planning in Many Dimensions - Extended Version.

Lucas Janson, Marco Pavone

CoRR, 2013

Fast Marching Trees: A Fast Marching Sampling-Based Method for Optimal Motion Planning in Many Dimensions.

Lucas Janson, Marco Pavone

Proceedings of the Robotics Research, 2013