3 papers
cs.RO2026
Massive Parallel Deep Reinforcement Learning for Active SLAM
Martín Arce Llobera, Julio A. Placed, Mariano De Paula +1
Recent advances in parallel computing and GPU acceleration have created new opportunities for computation-intensive learning problems such as Active SLAM -- where actions are selec…
cs.NI2026
LEO Topology Design Under Real-World Deployment Constraints
Muaz Ali, Beichuan Zhang
The performance of large-scale Low-Earth-Orbit (LEO) networks, which consist of thousands of satellites interconnected by optical links, is dependent on its network topology. Exist…
cs.IR2024
Full Stage Learning to Rank: A Unified Framework for Multi-Stage Systems
Kai Zheng, Haijun Zhao, Rui Huang +6
The Probability Ranking Principle (PRP) has been considered as the foundational standard in the design of information retrieval (IR) systems. The principle requires an IR module's…