论文标题
与无限二级输出空间的正规化最小二乘回归
Regularised Least-Squares Regression with Infinite-Dimensional Output Space
论文作者
论文摘要
这份简短的技术报告介绍了一些学习理论的结果，这些结果是关于矢量价值的繁殖核Hilbert Space（RKHS）回归的，其中允许输入空间是非紧凑的，并且输出空间是（可能是无限二维的）Hilbert Space。我们的方法是基于使用光谱理论的非compact运算符的积分操作员技术。我们特别强调以尽可能少的假设获得结果。因此，我们只使用Chebyshev的不平等，并且没有努力获得最佳的价格或常数。
This short technical report presents some learning theory results on vector-valued reproducing kernel Hilbert space (RKHS) regression, where the input space is allowed to be non-compact and the output space is a (possibly infinite-dimensional) Hilbert space. Our approach is based on the integral operator technique using spectral theory for non-compact operators. We place a particular emphasis on obtaining results with as few assumptions as possible; as such we only use Chebyshev's inequality, and no effort is made to obtain the best rates or constants.
