Human consciousness has been a long-lasting mystery for centuries, while...
Generating human-like behavior on robots is a great challenge especially...
Open-vocabulary object detection aims to provide object detectors traine...
Monocular 3D lane detection is a challenging task due to its lack of dep...
Panoptic Narrative Grounding (PNG) is an emerging task whose goal is to
...
This paper proposes novel, end-to-end deep reinforcement learning algori...
Referring video object segmentation aims to predict foreground labels fo...
This paper investigates the network load balancing problem in data cente...
This paper presents the network load balancing problem, a challenging
re...
Network load balancers are central components in data centers, that
dist...
Domain randomization (DR) cannot provide optimal policies for adapting t...
Language-queried video actor segmentation aims to predict the pixel-leve...
Deep reinforcement learning (DRL) has successfully solved various proble...
Learning an accurate model of the environment is essential for model-bas...
Reinforcement Learning (RL) methods have been widely applied for robotic...
Reinforcement learning (RL) has demonstrated great success in the past
s...
Deep Reinforcement Learning (DRL) has recently achieved significant adva...
Recently, we have seen a rapidly growing adoption of Deep Reinforcement
...
Zero-shot sim-to-real transfer of tasks with complex dynamics is a highl...
Deep learning and reinforcement learning methods have been shown to enab...
Learning agents that are not only capable of taking tests but also innov...
Deep generative models have been successfully applied to many applicatio...
Intelligent Transportation Systems (ITSs) are envisioned to play a criti...