论文标题
深度学习中的黑魔法：人类技能如何影响网络培训
Black Magic in Deep Learning: How Human Skill Impacts Network Training
论文作者
论文摘要
用户对深度学习影响准确性的先前经验如何？我们根据31名参与者提供了一项初步研究，具有不同的经验水平。他们的任务是针对给定的深度学习体系结构执行超参数优化。结果表明，参与者的经验与最终表现之间存在很强的正相关关系。他们还表明，有经验的参与者平均使用更少的资源找到了更好的解决方案。数据进一步表明，没有事先经验的参与者遵循随机策略追求最佳的超参数。我们的研究研究了艺术成果状态的比较和深度学习中的科学可重复性的主观人为因素。
How does a user's prior experience with deep learning impact accuracy? We present an initial study based on 31 participants with different levels of experience. Their task is to perform hyperparameter optimization for a given deep learning architecture. The results show a strong positive correlation between the participant's experience and the final performance. They additionally indicate that an experienced participant finds better solutions using fewer resources on average. The data suggests furthermore that participants with no prior experience follow random strategies in their pursuit of optimal hyperparameters. Our study investigates the subjective human factor in comparisons of state of the art results and scientific reproducibility in deep learning.
