locuslab/icnn

Help needed with Proposition 1 of your paper

ctrlmk opened this issue · 1 comments

Hi,
I have trouble understanding the proof of Proposition 1 of your paper (https://arxiv.org/pdf/1609.07152.pdf). Can you provide supplementary steps why a fully connected ICNN (defined in equation (2) of your paper) is convex. Especially, why W^(y)_i can have negative values?
For example, when setting all W^(z)_i = 0 I expect the network not to be convex in general.

I would appreciate any help. Thanks.

Please refer to my paper, which has the answer you want. 《Nonlinear model predictive control of USC boiler-turbine power units in flexible operations via input convex neural network》