Towards better robustness against common corruptions for unsupervised domain adaptation
Recent studies have investigated how to achieve robustness for unsupervised domain
adaptation (UDA). While most efforts focus on adversarial robustness, ie how the model …
adaptation (UDA). While most efforts focus on adversarial robustness, ie how the model …
Can chatgpt enable its? the case of mixed traffic control via reinforcement learning
The surge in Reinforcement Learning (RL) applications in Intelligent Transportation Systems
(ITS) has contributed to its growth as well as highlighted key challenges. However, defining …
(ITS) has contributed to its growth as well as highlighted key challenges. However, defining …
Inverse reinforcement learning with hybrid-weight trust-region optimization and curriculum learning for autonomous maneuvering
Despite significant advancements, collision-free navigation in autonomous driving is still
challenging, considering the navigation module needs to balance learning and planning to …
challenging, considering the navigation module needs to balance learning and planning to …
Variational Adversarial Defense: A Bayes Perspective for Adversarial Training
Various methods have been proposed to defend against adversarial attacks. However, there
is a lack of enough theoretical guarantee of the performance, thus leading to two problems …
is a lack of enough theoretical guarantee of the performance, thus leading to two problems …
Analyzing emissions and energy efficiency in mixed traffic control at unsignalized intersections
Greenhouse gas emissions have dramatically risen since the early 1900s with US
transportation generating 28% of the US'emissions. As such, there is interest in reducing …
transportation generating 28% of the US'emissions. As such, there is interest in reducing …
Mixed traffic control and coordination from pixels
Traffic congestion is a persistent problem in our society. Previous methods for traffic control
have proven futile in alleviating current congestion levels leading researchers to explore …
have proven futile in alleviating current congestion levels leading researchers to explore …
Extracting robust models with uncertain examples
Model extraction attacks are proven to be a severe privacy threat to Machine Learning as a
Service (MLaaS). A variety of techniques have been designed to steal a remote machine …
Service (MLaaS). A variety of techniques have been designed to steal a remote machine …
Learning to control dc motor for micromobility in real time with reinforcement learning
Autonomous micromobility has been attracting the attention of researchers and practitioners
in recent years. A key component of many micro-transport vehicles is the DC motor, a …
in recent years. A key component of many micro-transport vehicles is the DC motor, a …
CARL: Congestion-Aware Reinforcement Learning for Imitation-based Perturbations in Mixed Traffic Control
Human-driven vehicles (HVs) exhibit complex and diverse behaviors. Accurately modeling
such behavior is crucial for validating Robot Vehicles (RVs) in simulation and realizing the …
such behavior is crucial for validating Robot Vehicles (RVs) in simulation and realizing the …
Human body measurement estimation with adversarial augmentation
We present a Body Measurement network (BMnet) for estimating 3D anthropomorphic
measurements of the human body shape from silhouette images. Training of BMnet is …
measurements of the human body shape from silhouette images. Training of BMnet is …