steinwart_support_2008

Statistical Learning Theory 的本质

与经典的参数化方法不同,参数化方法假设 x 和 y 的关系服从某个确定性的函数。 (p3) this is a fundamental difference from parametric models, in which the relationship between the inputs x and the outputs y is assumed to follow some unknown function f ∈ F from a known, finite-dimensional set of functions F.

  • assuming that the output value y to a given x is stochastically generated by P( · |x) accommodates the fact that in general the information contained in x may not be sufficient to determine a single response in a deterministic manner.
  • assuming that the conditional probability P( · |x) is unknown contributes to the fact that we assume that we do not have a reasonable description of the relationship between the input and output values.

SVM 和 GP 的关系

For a brief description of kernel ridge regression and Gaussian processes, see Cristianini and Shawe-Taylor (2000, Section 6.2).

We refer to Wahba (1999) for the relationship between SVMs and Gaussian processes.

积累的一些小软件

名称 作用
Language Switcher 自定义打开软件时使用的语言环境设置
~~TinkerTool 设置Eclipse的系统相关字体大小 ~~(2019/03开始放弃使用Eclispe了)
QBlocker 防止误操作关闭。有时候会失效
~~清歌输入法 使用还算可以的五笔输入法~~
搜狗五笔
HyperSwitch 增强切换窗口

放弃解决的一些问题

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brack_inorbit_2017

In-Orbit Tracking of High Area-to-Mass Ratio Space Objects

这篇的intro介绍了许多新内容,值得学习

Singla, Puneet. 2016. “Certain Thoughts on Uncertainty Analysis for Dynamical Systems.” Department of Mechanical and Aerospace Engineering, University of Texas at Arlington, August 17. http://lairs.eng.buffalo.edu/wiki/images/a/ac/SinglaTalk.pdf.

The fusion of observational data with numerical simulation promises to provide greater understanding of physical phenomenon than either approach alone can achieve.

The most critical challenge here is to provide a quantitative assessment of how closely our estimates reflect reality in the presence of model uncertainty as well as measurement errors and uncertainty.

Uncertainty Propagation: Nonlinear Systems

  • Approximate Solution to exact problem: Multiple-model estimation method, Unscented Kalman Filter (UKF), Monte Carlo (MC) methods.
  • Exact solution to approximate problem: Extended Kalman Filter (EKF), Gaussian closure, Stochastic Linearization…

这两者的区别在哪里?为什么EKF是exact solution?

Fokker-Planck-Kolmogorov equation (FPKE)

With sufficient number of Gaussian components, any pdf can be approximated as closely as desired.

神经网络工具箱学习摘要

both shallow and deep NN

  • classification
  • regression (这里主要是针对这部分功能的学习摘要,其它网络还有很多不同的内容)
  • clustering
  • dimensionality reducetion
  • time-series forecasting: long short-term memory (LSTM) deep learning networks
  • dynamic system modeling and control

For small training sets, you can quickly apply deep learning by performing transfer learning with pretrained deep network models (GoogLeNet, AlexNet, VGG-16, and VGG-19) and models from the Caffe Model Zoo. (什么东西?)

支持 CPU 和 GPU 并行 支持 Amazon EC2 P2 GPU instances (是什么?)

主要函数

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