4 citations · 8 across the 3 of their papers we have counts for
3 papers
Personalized Federated Learning of Driver Prediction Models for Autonomous Driving
Manabu Nakanoya, Junha Im, Hang Qiu +3
Autonomous vehicles (AVs) must interact with a diverse set of human drivers in heterogeneous geographic areas. Ideally, fleets of AVs should share trajectory data to continually re…
Sampling Training Data for Continual Learning Between Robots and the Cloud
Sandeep Chinchali, Evgenya Pergament, Manabu Nakanoya +5
Today's robotic fleets are increasingly measuring high-volume video and LIDAR sensory streams, which can be mined for valuable training data, such as rare scenes of road constructi…
Task-relevant Representation Learning for Networked Robotic Perception
Manabu Nakanoya, Sandeep Chinchali, Alexandros Anemogiannis +3
Today, even the most compute-and-power constrained robots can measure complex, high data-rate video and LIDAR sensory streams. Often, such robots, ranging from low-power drones to…