ECOLE 2018 Tutorial机器学习中的优化问题简介
Artificial intelligence systems，machine learning improves system performance automatically from experience.provides tools for intelligent data analysis.learning task category：supervised learning、partially supervised learning、reinforcement learning、unsupervised learning.a typical formulation：value function approximation directly find the parameters of the policy.supervised/partially supervised learning.machine learning=representation + evaluation + optimization.highly complex functions vs. gradient-based methods，relax to convex problems，convex loss functions are noise-sensitive ”Long and Servedio, MLJ”OO”，convex regularizations are not consistent ”Fan and Li, JASA”O1”，hard to be relaxed.
机器学习 优化问题 监督学习
俞扬
南京大学 软件新技术国家重点实验室 计算机科学与技术系|人工智能学院
国内会议
广州
中文
1-54
2018-05-18（万方平台首次上网日期，不代表论文的发表时间）