Viewing profile — human_scientist

> To submit to arxiv you need to be approved by someone as a legitimate researcher, or beg for reviews from people you’ve never met without any anonymity. I did not have to do some…

It depends on the number of evaluations. The more evaluations the stronger the model built by the TPE algorithm. With very few evaluations, we would expect TPE to match random samp…

HyperOpt is a library for hyperparameter optimization, my comment was about algorithms. From the homepage of hyperopt: "Currently two algorithms are implemented in hyperopt: Random…

What is the expected lifetime?

Nice project! You use gridsearch for hyperparamter optimization and state that at some point you would like to add a bayesian approach. One simple change that could boost the perfo…

The NFL only applies to settings where your task distribution is uniform random over all possible tasks. It is my intuition that this kind of task distribution is almost surely not…

Your algorithm description sounds like a variant of greedy local search with a NN heuristic. While I personaly do not know of a paper that does this kind of local search (I have no…

> I don't see "Automatic design of novel algorithms" in this list. Can AutoML produce something as novel as a GAN, CapsNet, WaveNet, Transformer, Neural ODE, etc? Is that even cons…

The field of automatic machine learning (abbreviated as AutoML) concerns all endeavours to automate the process of machine learning. To provide a sense of what could constitute Aut…

Why? The concept of AutoML does include the design of novel algorithms.

Could you give an example? I have a hard time understanding what you could mean, as Algorithm Configuration & Selection is such a general framework. If you are solely talking about…

The parent did not specifically talk about NNs. As I understand it AutoML could apply to all statistical endeavours that involve estimation (classical or bayesian).

Automatically building a scikit learn estimator might include many conditional hyperparameters and also a very large amount of them ( The tools included in the repository are very …

What about approaches like auto-sklearn [1]? With these it is basicaly: >>> automl = autosklearn.classification.AutoSklearnClassifier() >>> automl.fit(X_train, y_train) >>> y_hat =…

https://eternagame.org/ This is RNA Design for humans as a game! Also: A trained human outperforms current AI approaches for RNA Design.