Skip to main content
edited title
Link
Juho
  • 22.8k
  • 7
  • 62
  • 117

Unknown notation "$e^T$" in a machine-learning learning paper

Tweeted twitter.com/#!/StackCompSci/status/453218355408011264
edited tags
Link
Raphael
  • 72.9k
  • 30
  • 181
  • 393

Unknown notation "$e^T$" in SVM / Dual optimisationmachine-learning paper

Source Link

Unknown notation in SVM / Dual optimisation paper

I'm trying to understand the material in "A Dual Coordinate Descent Method for Large-scale Linear SVM" by Hsieh et. al. (link to paper) There is an equation for the Dual form of an unconstrained optimisation problem,

$$ f(\mathbf{\alpha})=\dfrac{1}{2}\mathbf{\alpha}^T\bar{Q}\alpha-e^T\alpha $$

I don't understand what the $\mathbf{e}^T$ means, it's not explained in the surronding text, so I assume it's just some common notation. Later in the paper $\mathbf{e}_i$ is defined as $\mathbf{e}_i=[0,\ldots,1,0,\ldots,0]^T$, so maybe it's some sort of selector term? Not sure if this second mention is even related.

Please may someone explain to be what the $\mathbf{e}^T$ bit is doing in this formula? Thank you for your time.