fernandocamargoti
fernandocamargoti t1_j5zs45e wrote
Reply to comment by new_name_who_dis_ in [P] EvoTorch 0.4.0 dropped with GPU-accelerated implementations of CMA-ES, MAP-Elites and NSGA-II. by NaturalGradient
They not about learning from data, they are about optimization. They are from the broader AI field of study, but I wouldn't say they are ML. They serve a different purpose. Even though there are some research about using them to optimize models (instead of using gradient descent), but it's not their main use case.
fernandocamargoti t1_j5z4qpc wrote
Reply to comment by ML4Bratwurst in [P] EvoTorch 0.4.0 dropped with GPU-accelerated implementations of CMA-ES, MAP-Elites and NSGA-II. by NaturalGradient
Evolutionary algorithms are not ML.
fernandocamargoti t1_irc04s7 wrote
Very interesting. How would you compare your project to https://github.com/KevinMusgrave/pytorch-metric-learning?
fernandocamargoti t1_j60xagg wrote
Reply to comment by ReginaldIII in [P] EvoTorch 0.4.0 dropped with GPU-accelerated implementations of CMA-ES, MAP-Elites and NSGA-II. by NaturalGradient
Well, what you talking about is some ways to use evolutionary algorithms to optimize the parameters of a ML model. But in my eyes, it doesn't mean it is ML. They both share a lot, but they aren't the same. For me, evolutionary algorithms is part of Meta Heuristics, which is part of AI (which ML is also part of). Different areas and sub areas of research do interact with each other. I just mean that the is part is a bit too much in this case.