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.


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~~
HyperSwitch 增强切换窗口


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


Singla, Puneet. 2016. “Certain Thoughts on Uncertainty Analysis for Dynamical Systems.” Department of Mechanical and Aerospace Engineering, University of Texas at Arlington, August 17.

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.


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?)


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