… is still required to bring about full autonomy. The future of the … as truck-configurationagnostic
longitudinal modeling and … presents learning curves for training the deep truck model for …

… In this research, we propose a deep learning-based image … In [40], the authors trained a
deep neural network to learn the … that the convergence is configuration agnostic. Moreover, the …

… Reinforcement Learning (RL), in which an agent is trained to … use, an application and
resource configuration agnostic … Owing to the commercial and research interest in autonomous …

… We study the ability of autonomous vehicles to improve the … nested feedback loops in the
model for training. We compare this … -RL as an alternative; a configuration agnostic strategy for …

… However, we want to achieve the autonomous behavior in the … Similarly, the models can
be trained in online or offline … models, game-theoretic models and machine learning based …

… entities that are capable of autonomous decision making, real… AI-driven (machine learning),
trained algorithms that predict (… adoption of a machine- and configuration-agnostic approach. …

… pinch grasp locations, and execute grasps autonomously with little or no information from …
This thesis attempts to leverage machine learning techniques to train a system to recognize, …

… You are some of the best people I have met during my studies course. A special mention …
The Service concept refers to an independent and (possibly) autonomous computing entity, …

… [12], a multi-level deep learning approach that combines a … GNN models have a unique
configuration-agnostic feature. A … GNN model, namely its training does not require a large data set…

… VMs require autonomous control of host resources. Our … Our scheme is both application and
configuration agnostic. … How to train the scaling agent—After having trained the AC, we need …