Trial-based dominance for comparing both the speed and accuracy of stochastic optimizers with standard non-parametric tests حسب Kenneth V. Price (17877002)

"…<p>Non-parametric tests can determine the better of two stochastic optimization algorithms when benchmarking results are ordinal—like the final fitness values of multiple trials—but for many benchmarks, a trial can also terminate once it reaches a prespecified target value. …"

Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms حسب Marwan Dhuheir (19170898)

"…Distributed inference enabled via swarms of collaborative UAVs presents a promising solution by partitioning tasks among UAVs based on their available resources, allowing for more efficient, collaborative processing. …"