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In addition to the other good answer, if you can afford the luxury of running your experiments multiple times, you can also use hypothesis testing to test whether there is any significant difference between the performance (e.g. accuracy) of the two models. Hypothesis testing is not widely used (or, at least, reported in research papers) in the ML/DL ...


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I wonder how expert AI researchers deal with that, do they perform multiple experiments, even if this takes extremely long? Do they draw conclusions from single runs? Unfortunately, the question you ask in the main body of your question here ("how do expert AI researchers do things") often turns out to actually be different from the question in ...


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You can find information similar to exposed by Neil, but with more theoretical detail, in the book Deep Learning (Goodfellow et al., 2016) in the chapter 10 (Recurrent networks), more specifically in 10.2.3 Recurrent Networks as Directed Graphical Models and other subchapters. Additional, related with pointer networks there are people changing the LSTM with ...


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I do not think there is one standard way to do this, it will depend too much on context. Ultimately you want the agent to output a stop action that is different from a continue action. That stop/continue choice could either be part of the existing action encoding, additional data in parallel with the action sequence, or an entirely separate action choice on ...


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What you are suggesting is similar to active learning and reward modelling. To summarize both quickly, active learning is used when data are scarce or when the labeling process is too time consuming (almost always the case in NLP). To speed up the process, the idea is to train a model in performing not only a task, but also an estimation of its uncertainty ...


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That's a very nice challenge! As always, the hardest part is to get a labeled database (maybe by scrapping). You'd probably need some thousands of drawings and their respective drawer age. From there, you need to make an image regression model. Here is a simple example that predicts age from a face photo. It's the same principle, but applied to another ...


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