We introduce novel discriminative learning algorithms for dynamical systems. Models such as Conditional Random Fields or Maximum Entropy Markov Models outperform the generative Hi...
We recently proposed a new approach to parallelization, by decomposing the time domain, instead of the conventional space domain. This improves latency tolerance, and we demonstrat...
Action modeling is an important skill for agents that must perform tasks in novel domains. Previous work on action modeling has focused on learning STRIPS operators in discrete, r...
This paper introduces a new programming model for distributed systems, distributed composite objects (DCO), to meet efficient implementation, transparency, and performance demands ...
— This paper outlines a novel and feasible procedure to predict vertical motions for safe landing of unmanned aerial vehicles (UAVs) during maritime operations. In the presence o...
Xilin Yang, Hemanshu Roy Pota, Matthew Garratt, Va...