Lucas Janson

55 papers A* 12A 2C 1Journal 34Unranked 6
YearRankTypeTitle / Venue / Authors
2025 A* conf
A New Perspective on Shampoo's Preconditioner.
ICLR
Depen Morwani, Itai Shapira, Nikhil Vyas, Eran Malach, Sham M. Kakade, Lucas Janson
2025 A* conf
Context in Public Health for Underserved Communities: A Bayesian Approach to Online Restless Bandits.
AAAI
Biyonka Liang, Lily Xu, Aparna Taneja, Milind Tambe, Lucas Janson
2025 J jnl
Estimating the Convex Hull of the Image of a Set with Smooth Boundary: Error Bounds and Applications.
Discret. Comput. Geom.
Thomas Lew, Riccardo Bonalli, Lucas Janson, Marco Pavone
2025 A* conf
Evaluating Index-based Treatment Allocation in Underresourced Communities.
AAAI
Niclas Boehmer, Yash Nair, Sanket Shah, Lucas Janson, Aparna Taneja, Milind Tambe
2025 J jnl
Foundations of Safe Online Reinforcement Learning in the Linear Quadratic Regulator: √T-Regret.
CoRR
Benjamin Schiffer, Lucas Janson
2025 A* conf
SOAP: Improving and Stabilizing Shampoo using Adam for Language Modeling.
ICLR
Nikhil Vyas, Depen Morwani, Rosie Zhao, Itai Shapira, David Brandfonbrener, Lucas Janson, Sham M. Kakade
2025 J jnl
Surrogate-Based Global Sensitivity Analysis with Statistical Guarantees via Floodgate.
SIAM/ASA J. Uncertain. Quantification
Massimo Aufiero, Lucas Janson
2025 J jnl
The Relative Instability of Model Comparison with Cross-validation.
CoRR
Alexandre Bayle, Lucas Janson, Lester Mackey
2024 J jnl
A Bayesian Approach to Online Learning for Contextual Restless Bandits with Applications to Public Health.
CoRR
Biyonka Liang, Lily Xu, Aparna Taneja, Milind Tambe, Lucas Janson
2024 J jnl
A New Perspective on Shampoo's Preconditioner.
CoRR
Depen Morwani, Itai Shapira, Nikhil Vyas, Eran Malach, Sham M. Kakade, Lucas Janson
2024 J jnl
Evaluating the Effectiveness of Index-Based Treatment Allocation.
CoRR
Niclas Boehmer, Yash Nair, Sanket Shah, Lucas Janson, Aparna Taneja, Milind Tambe
2024 A* conf
Optimal ablation for interpretability.
NeurIPS
Maximilian Li, Lucas Janson
2024 J jnl
Optimal ablation for interpretability.
CoRR
Maximilian Li, Lucas Janson
2024 J jnl
SOAP: Improving and Stabilizing Shampoo using Adam.
CoRR
Nikhil Vyas, Depen Morwani, Rosie Zhao, Itai Shapira, David Brandfonbrener, Lucas Janson, Sham M. Kakade
2024 J jnl
Stronger Regret Bounds for Safe Online Reinforcement Learning in the Linear Quadratic Regulator.
CoRR
Benjamin Schiffer, Lucas Janson
2024 A* conf
Total Variation Floodgate for Variable Importance Inference in Classification.
ICML
Wenshuo Wang, Lucas Janson, Lihua Lei, Aaditya Ramdas
2023 J jnl
Estimating the convex hull of the image of a set with smooth boundary: error bounds and applications.
CoRR
Thomas Lew, Riccardo Bonalli, Lucas Janson, Marco Pavone
2023 — conf
Rate-Matching the Regret Lower-Bound in the Linear Quadratic Regulator with Unknown Dynamics.
CDC
Feicheng Wang, Lucas Janson
2022 — conf
A Simple and Efficient Sampling-based Algorithm for General Reachability Analysis.
L4DC
Thomas Lew, Lucas Janson, Riccardo Bonalli, Marco Pavone
2022 J jnl
Rate-matching the regret lower-bound in the linear quadratic regulator with unknown dynamics.
CoRR
Feicheng Wang, Lucas Janson
2022 J jnl
Statistical Inference After Adaptive Sampling in Non-Markovian Environments.
CoRR
Kelly W. Zhang, Lucas Janson, Susan A. Murphy
2022 A conf
The Role of Tactile Sensing in Learning and Deploying Grasp Refinement Algorithms.
IROS
Alexander Koenig, Zixi Liu, Lucas Janson, Robert D. Howe
2021 J jnl
A Simple and Efficient Sampling-based Algorithm for General Reachability Analysis.
CoRR
Thomas Lew, Lucas Janson, Riccardo Bonalli, Marco Pavone
2021 J jnl
A statistical model for describing and simulating microbial community profiles.
PLoS Comput. Biol.
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
2021 J jnl
Exact Asymptotics for Linear Quadratic Adaptive Control.
J. Mach. Learn. Res.
Feicheng Wang, Lucas Janson
2021 A* conf
Statistical Inference with M-Estimators on Adaptively Collected Data.
NeurIPS
Kelly W. Zhang, Lucas Janson, Susan A. Murphy
2021 J jnl
Statistical Inference with M-Estimators on Bandit Data.
CoRR
Kelly W. Zhang, Lucas Janson, Susan A. Murphy
2021 J jnl
Tactile Grasp Refinement using Deep Reinforcement Learning and Analytic Grasp Stability Metrics.
CoRR
Alexander Koenig, Zixi Liu, Lucas Janson, Robert D. Howe
2020 A* conf
Cross-validation Confidence Intervals for Test Error.
NeurIPS
Pierre Bayle, Alexandre Bayle, Lucas Janson, Lester Mackey
2020 J jnl
Cross-validation Confidence Intervals for Test Error.
CoRR
Pierre Bayle, Alexandre Bayle, Lucas Janson, Lester Mackey
2020 J jnl
Exact Asymptotics for Linear Quadratic Adaptive Control.
CoRR
Feicheng Wang, Lucas Janson
2020 A* conf
Inference for Batched Bandits.
NeurIPS
Kelly W. Zhang, Lucas Janson, Susan A. Murphy
2020 J jnl
Inference for Batched Bandits.
CoRR
Kelly W. Zhang, Lucas Janson, Susan A. Murphy
2020 A* conf
Map-Predictive Motion Planning in Unknown Environments.
ICRA
Amine Elhafsi, Boris Ivanovic, Lucas Janson, Marco Pavone
2020 A* conf
Revisiting the Asymptotic Optimality of RRT.
ICRA
Kiril Solovey, Lucas Janson, Edward Schmerling, Emilio Frazzoli, Marco Pavone
2019 J jnl
Map-Predictive Motion Planning in Unknown Environments.
CoRR
Amine Elhafsi, Boris Ivanovic, Lucas Janson, Marco Pavone
2019 J jnl
Revisiting the Asymptotic Optimality of RRT.
CoRR
Kiril Solovey, Lucas Janson, Edward Schmerling, Emilio Frazzoli, Marco Pavone
2018 J jnl
Deterministic sampling-based motion planning: Optimality, complexity, and performance.
Int. J. Robotics Res.
Lucas Janson, Brian Ichter, Marco Pavone
2018 — conf
Safe Motion Planning in Unknown Environments: Optimality Benchmarks and Tractable Policies.
Robotics: Science and Systems
Lucas Janson, Tommy Hu, Marco Pavone
2018 J jnl
Safe Motion Planning in Unknown Environments: Optimality Benchmarks and Tractable Policies.
CoRR
Lucas Janson, Tommy Hu, Marco Pavone
2017 J jnl
Risk-Constrained Reinforcement Learning with Percentile Risk Criteria.
J. Mach. Learn. Res.
Yinlam Chow, Mohammad Ghavamzadeh, Lucas Janson, Marco Pavone
2015 J jnl
An Asymptotically-Optimal Sampling-Based Algorithm for Bi-directional Motion Planning.
CoRR
Joseph A. Starek, Javier V. Gómez, Edward Schmerling, Lucas Janson, Luis Moreno, Marco Pavone
2015 A conf
An asymptotically-optimal sampling-based algorithm for Bi-directional motion planning.
IROS
Joseph A. Starek, Javier V. Gómez, Edward Schmerling, Lucas Janson, Luis Moreno, Marco Pavone
2015 — conf
Deterministic Sampling-Based Motion Planning: Optimality, Complexity, and Performance.
ISRR (2)
Lucas Janson, Brian Ichter, Marco Pavone
2015 J jnl
Deterministic Sampling-Based Motion Planning: Optimality, Complexity, and Performance.
CoRR
Lucas Janson, Brian Ichter, Marco Pavone
2015 J jnl
Fast marching tree: A fast marching sampling-based method for optimal motion planning in many dimensions.
Int. J. Robotics Res.
Lucas Janson, Edward Schmerling, Ashley A. Clark, Marco Pavone
2015 — conf
Monte Carlo Motion Planning for Robot Trajectory Optimization Under Uncertainty.
ISRR (2)
Lucas Janson, Edward Schmerling, Marco Pavone
2015 J jnl
Monte Carlo Motion Planning for Robot Trajectory Optimization Under Uncertainty.
CoRR
Lucas Janson, Edward Schmerling, Marco Pavone
2015 — conf
Optimal sampling-based motion planning under differential constraints: The drift case with linear affine dynamics.
CDC
Edward Schmerling, Lucas Janson, Marco Pavone
2015 A* conf
Optimal sampling-based motion planning under differential constraints: The driftless case.
ICRA
Edward Schmerling, Lucas Janson, Marco Pavone
2015 J jnl
Risk-Constrained Reinforcement Learning with Percentile Risk Criteria.
CoRR
Yinlam Chow, Mohammad Ghavamzadeh, Lucas Janson, Marco Pavone
2014 J jnl
Optimal Sampling-Based Motion Planning under Differential Constraints: the Drift Case with Linear Affine Dynamics.
CoRR
Edward Schmerling, Lucas Janson, Marco Pavone
2014 J jnl
Optimal Sampling-Based Motion Planning under Differential Constraints: the Driftless Case.
CoRR
Edward Schmerling, Lucas Janson, Marco Pavone
2013 C conf
Fast Marching Trees: A Fast Marching Sampling-Based Method for Optimal Motion Planning in Many Dimensions.
ISRR
Lucas Janson, Marco Pavone
2013 J jnl
Fast Marching Trees: a Fast Marching Sampling-Based Method for Optimal Motion Planning in Many Dimensions - Extended Version.
CoRR
Lucas Janson, Marco Pavone