Search Results for author: Roy Dong

Found 13 papers, 0 papers with code

Distribution-Free Guarantees for Systems with Decision-Dependent Noise

no code implementations2 Mar 2024 Heling Zhang, Lillian J. Ratliff, Roy Dong

Our approach finds the open-loop control law that minimizes the worst-case loss, given that the noise induced by this control lies in its $(1 - p)$-confidence set for a predetermined $p$.

Conformal Prediction

Incentive Design for Eco-driving in Urban Transportation Networks

no code implementations7 Nov 2023 M. Umar B. Niazi, Jung-Hoon Cho, Munther A. Dahleh, Roy Dong, Cathy Wu

Eco-driving emerges as a cost-effective and efficient strategy to mitigate greenhouse gas emissions in urban transportation networks.

Hybrid System Stability Analysis of Multi-Lane Mixed-Autonomy Traffic

no code implementations11 Oct 2023 Sirui Li, Roy Dong, Cathy Wu

Through examining the influence of the lane-switch frequency on the system's stability, the analysis offers a principled explanation to the traffic break phenomena, and further discovers opportunities for less-intrusive traffic smoothing by employing less frequent lane-switching.

Autonomous Vehicles

Identifying Single-Input Linear System Dynamics from Reachable Sets

no code implementations8 Sep 2023 Taha Shafa, Roy Dong, Melkior Ornik

This paper is concerned with identifying linear system dynamics without the knowledge of individual system trajectories, but from the knowledge of the system's reachable sets observed at different times.

Integrated Analysis of Coarse-Grained Guidance for Traffic Flow Stability

no code implementations10 Jan 2023 Sirui Li, Roy Dong, Cathy Wu

While previous theoretical studies consider stability analysis for continuous AV control, this article presents the first integrated theoretical analysis that directly relates the guidance provided to the human drivers to the traffic flow stability outcome.

Autonomous Vehicles

Approximate Regions of Attraction in Learning with Decision-Dependent Distributions

no code implementations30 Jun 2021 Roy Dong, Heling Zhang, Lillian J. Ratliff

As data-driven methods are deployed in real-world settings, the processes that generate the observed data will often react to the decisions of the learner.

Improving the Feasibility of Moment-Based Safety Analysis for Stochastic Dynamics

no code implementations11 Apr 2021 Peter Du, Katherine Driggs-Campbell, Roy Dong

We then reformulate the constraints of the optimization to mitigate the computational limitations associated with an increase in state dimensionality.

On the Sample Complexity of Causal Discovery and the Value of Domain Expertise

no code implementations5 Feb 2021 Samir Wadhwa, Roy Dong

Causal discovery methods seek to identify causal relations between random variables from purely observational data, as opposed to actively collected experimental data where an experimenter intervenes on a subset of correlates.

Causal Discovery

Private DNA Sequencing: Hiding Information in Discrete Noise

no code implementations28 Jan 2021 Kayvon Mazooji, Roy Dong, Ilan Shomorony

When an individual's DNA is sequenced, sensitive medical information becomes available to the sequencing laboratory.

Information Theory Cryptography and Security Information Theory

Expert Selection in High-Dimensional Markov Decision Processes

no code implementations26 Oct 2020 Vicenc Rubies-Royo, Eric Mazumdar, Roy Dong, Claire Tomlin, S. Shankar Sastry

In this work we present a multi-armed bandit framework for online expert selection in Markov decision processes and demonstrate its use in high-dimensional settings.

Vocal Bursts Intensity Prediction

Competitive Statistical Estimation with Strategic Data Sources

no code implementations29 Apr 2019 Tyler Westenbroek, Roy Dong, Lillian J. Ratliff, S. Shankar Sastry

Recent work has explored mechanisms to ensure that the data sources share high quality data with a single data aggregator, addressing the issue of moral hazard.

A Multi-Armed Bandit Approach for Online Expert Selection in Markov Decision Processes

no code implementations18 Jul 2017 Eric Mazumdar, Roy Dong, Vicenç Rúbies Royo, Claire Tomlin, S. Shankar Sastry

We formulate a multi-armed bandit (MAB) approach to choosing expert policies online in Markov decision processes (MDPs).

Systems and Control

CPRL -- An Extension of Compressive Sensing to the Phase Retrieval Problem

no code implementations NeurIPS 2012 Henrik Ohlsson, Allen Yang, Roy Dong, Shankar Sastry

This paper presents a novel extension of CS to the phase retrieval problem, where intensity measurements of a linear system are used to recover a complex sparse signal.

Compressive Sensing Retrieval

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