4 accepted papers
Generalization is one of the most fundamental challenges in deep learning, aiming to predict model performances on unseen data. Empirically, such predictions usually rely on a validation set, while recent works showed that an unlabeled validation set also works. Without validation sets, it is extrem…
In this paper, we consider the refuel scheduling problem for a team of ground robots deployed in "aislelike" environments wherein the robots are constrained to move along rows. In order to maintain a minimum service rate or throughput for the ground robots, we investigate the problem of scheduling a…
Image segmentation automatically segments a target object in an image and has recently achieved prominent progress due to the development of deep convolutional neural networks (DCNNs). However, the quality of manual labels plays an essential role in the segmentation accuracy, while in practice it co…
In this work, we address the problem of centralized scheduling and motion planning for multiple grain carts with finite capacity that serve a group of combine harvesters engaged in a harvesting operation. First, we solve a facility location problem of finding the optimal depot position to minimize t…