Low Budget

Low-budget research focuses on optimizing performance and efficiency within resource constraints, spanning diverse fields like machine learning, mechanism design, and telepresence. Current efforts concentrate on developing algorithms and models that achieve high accuracy or social efficiency with minimal computational cost or data, employing techniques such as Bayesian neural networks, early exit strategies, and efficient optimization heuristics. These advancements are significant for enabling reliable inference with expensive simulators, designing cost-effective social mechanisms, and creating accessible high-quality technologies, ultimately broadening the applicability of computationally intensive methods.