Search Results for author: Jung-Hoon Cho

Found 7 papers, 0 papers with code

The Nah Bandit: Modeling User Non-compliance in Recommendation Systems

no code implementations15 Aug 2024 Tianyue Zhou, Jung-Hoon Cho, Cathy Wu

It is thus crucial in cyber-physical recommendation systems to operate with an interaction model that is aware of such user behavior, lest the user abandon the recommendations altogether.

Recommendation Systems

Cooperative Advisory Residual Policies for Congestion Mitigation

no code implementations30 Jun 2024 Aamir Hasan, Neeloy Chakraborty, Haonan Chen, Jung-Hoon Cho, Cathy Wu, Katherine Driggs-Campbell

Our policies are trained in simulation with our novel instruction adherence driver model, and evaluated in simulation and through a user study (N=16) to capture the sentiments of human drivers.

Autonomous Vehicles

Expert with Clustering: Hierarchical Online Preference Learning Framework

no code implementations26 Jan 2024 Tianyue Zhou, Jung-Hoon Cho, Babak Rahimi Ardabili, Hamed Tabkhi, Cathy Wu

To the best of the authors knowledge, this is the first work to analyze the regret of an integrated expert algorithm with k-Means clustering.

Clustering

Temporal Transfer Learning for Traffic Optimization with Coarse-grained Advisory Autonomy

no code implementations27 Nov 2023 Jung-Hoon Cho, Sirui Li, Jeongyun Kim, Cathy Wu

We introduce Temporal Transfer Learning (TTL) algorithms to select source tasks for zero-shot transfer, systematically leveraging the temporal structure to solve the full range of tasks.

Reinforcement Learning (RL) Transfer Learning

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.

PeRP: Personalized Residual Policies For Congestion Mitigation Through Co-operative Advisory Systems

no code implementations1 Aug 2023 Aamir Hasan, Neeloy Chakraborty, Haonan Chen, Jung-Hoon Cho, Cathy Wu, Katherine Driggs-Campbell

To this end, we develop a co-operative advisory system based on PC policies with a novel driver trait conditioned Personalized Residual Policy, PeRP.

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