Web: https://www.reddit.com/r/MachineLearning/comments/sb62m9/d_nondifferentiable_loss_functions/

Jan. 23, 2022, 10:39 p.m. | /u/ottawalanguages

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Do Problems in Combinatorial Discrete Optimization (generally) Have Non-Differentiable Loss Functions?

I was trying to better understand this: we can only take the derivatives of functions if they have certain properties (https://en.wikipedia.org/wiki/Differentiable_function : e.g. continuous, no indicator variables within them, etc.).

Considering the nature of many typical problems in combinatorial discrete optimization (e.g. scheduling flights, shortest path, travelling salesmen problem, knapsack problem) - at first thought, it does not seem like the objective functions of these problems are "differentiable" …

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