Fixed Budget is No Harder Than Fixed Confidence in Best-Arm Identification up to Logarithmic Factors
Researchers have demonstrated that the fixed-budget setting in best-arm identification problems is no harder than the fixed-confidence setting, up to logarithmic factors. They developed a meta-algorithm called FC2FB that converts fixed-confidence algorithms into fixed-budget ones. This new approach can lead to improved sample complexity for various fixed-budget problems by leveraging existing state-of-the-art fixed-confidence algorithms. AI
IMPACT This research could lead to more efficient algorithms for problems involving sequential decision-making and exploration in machine learning.