论文标题
机器学习中的非平滑度：特定的结构，近端识别和应用
Nonsmoothness in Machine Learning: specific structure, proximal identification, and applications
论文作者
论文摘要
非平滑度通常是优化的诅咒。但这有时是一种祝福，特别是对于机器学习中的应用。在本文中，我们介绍了机器学习中出现的非平滑优化问题的特定结构，并说明了如何在实践中利用这种结构，以减少压缩，加速或尺寸。我们特别注意演示文稿，以简洁且易于访问，并以简单的示例和一般结果。
Nonsmoothness is often a curse for optimization; but it is sometimes a blessing, in particular for applications in machine learning. In this paper, we present the specific structure of nonsmooth optimization problems appearing in machine learning and illustrate how to leverage this structure in practice, for compression, acceleration, or dimension reduction. We pay a special attention to the presentation to make it concise and easily accessible, with both simple examples and general results.
