4 Matching Annotations
  1. Dec 2019
  2. Oct 2017
    1. ΔCΔC\Delta C in terms of ΔvΔv\Delta v and the gradient, ∇C

      ΔC not the same as ∇C.

      ΔC -> difference / changes

      ∇C -> gradient vector

  3. Apr 2016
    1. Effect of step size. The gradient tells us the direction in which the function has the steepest rate of increase, but it does not tell us how far along this direction we should step.

      That's the reason why step size is an important factor in optimization algorithm. Too small step can cause the algorithm longer to converge. Too large step can cause that we change the parameters too much thus overstepped the optima.

  4. Jan 2016
    1. This criterion is not based on any specific shape of the dose-response relationship.

      I would expect that the relationship must be monotonic to support the causal hypothesis.