Update landscape plot (#20)

* Add seed in landscape plot

* Update README.md

README.md

@@ -22,14 +22,14 @@ The utility provided by this package is the function `optfuns` which returns thr
 The code for this benchmark is in the `runtests.jl`.
 
 ## Visualize loss landscape
-We define a plot recipe such that a loss landscape can be plotted with
+Based on the work on [loss landscape visualization [2]](https://arxiv.org/abs/1712.09913), we define a plot recipe such that a loss landscape can be plotted with
 ```julia
 using Plots
-plot(loss, pars, l=0.1, npoints=50, seriestype=:contour)
+contourf(() -> log10(1 + loss()), pars, color=:turbo, npoints=50, lnorm=1)
 ```
 ![landscape](figs/landscape.svg)
 
-The landscape is plotted by selecting two random directions and extending the current point (`pars`) a distance `l*norm(pars)` (both negative and positive) along the two random directions. The number of loss evaluations will be `npoints^2`.
+The landscape is plotted by selecting two random directions and extending the current point (`pars`) a distance `lnorm * norm(pars)` (both negative and positive) along the two random directions. The number of loss evaluations will be `npoints^2`.
 
 
 ## Flatten and Unflatten
@@ -48,3 +48,5 @@ This is what is used under the hood in the functions returned from `optfuns` in
 
 # References
 [[1] "Stochastic quasi-Newton with adaptive step lengths for large-scale problems", Adrian Wills, Thomas Schön, 2018](https://arxiv.org/abs/1802.04310)
+
+[[2] "Visualizing the Loss Landscape of Neural Nets", Hao Li, Zheng Xu, Gavin Taylor, Christoph Studer, Tom Goldstein, 2018](https://arxiv.org/abs/1712.09913)