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1500 questions
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3 answers
Isn't a simulation a great model for model-based reinforcement learning?
Most reinforcement learning agents are trained in simulated environments. The goal is to maximize performance in (often) the same environment, preferably with a minimum amount of interactions. Having a good model of the environment allows to use…
Ray Walker
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Why do we need both the validation set and test set?
I know that this has been asked a hundred times before, however, I was not able to find a question (and an answer) which actually answered what I wanted to know, respectively, which explained it in a way I was able to understand. So, I'm trying to…
Golo Roden
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5
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How to add a dense layer after a 2d convolutional layer in a convolutional autoencoder?
I am trying to implement a convolutional autoencoder with a dense layer at the bottleneck to do some dimensional reduction. I have seen two approaches for this, which aren't particularly scalable. The first was to introduce 2 dense layers (one at…
Pavan Inguva
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Are Convolutional Neural Networks better than existing image recognition libraries that don't use CNNs?
Are Convolutional Neural Networks summarily better than pattern recognition in all existing image processing libraries that don't use CNN's? Or are there still hard outstanding problems in image processing that seem to be beyond their capability?
dynrepsys
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How could we define passion in artificial intelligence?
Mankind can create machines to do work. How could we define passion in artificial intelligence? How could we define a passionate AI?
Would passion cause the machine to do a better job? How could we compare the performance of a passionate machine, as…
D. Wade
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What effect does batch norm have on the gradient?
Batch norm is a technique where they essentially standardize the activations at each layer, before passing it on to the next layer. Naturally, this will affect the gradient through the network. I have seen the equations that derive the…
information_interchange
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What is the difference between evolutionary computation and evolutionary algorithms?
A book on evolutionary computation by De Jong mentions both the term evolutionary algorithms (EA) as well as evolutionary computation (EC). However, it remains unclear to me what the difference between the two is. According to Vikhar, EA forms a…
dan888
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How to calculate the advantage in policy gradient functions?
From my understanding of the REINFORCE policy gradient method, we gently nudge the probabilities of actions based on the advantages. More specifically, the positive advantages increase the probabilities, negative advantages reduce the…
Bob Kimani
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Is there any resource that describes in detail a naive example-based machine translation algorithm?
I'm looking to develop a machine translation tool for a constructed language. I think that the example-based approach is the most suitable because the said language is very regular and I can have a sufficient amount of parallel translations.
I…
user34314
5
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2 answers
How can the policy iteration algorithm be model-free if it uses the transition probabilities?
I'm actually trying to understand the policy iteration in the context of RL. I read an article presenting it and, at some point, a pseudo-code of the algorithm is given :
What I can't understand is this line :
From what I understand, policy…
Samuel Beaussant
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How to predict time series with accuracy?
I am trying to predict Forex time series. The nature of the market is that 80% of the time the price can not be predicted, but in 20% of the time it can be. For example, if the price drops down very deep, there is 99% probability that there will be…
Nulik
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How to replicate legacy systems with machine learning?
Let's suppose that we have a legacy system in which we don't have the source code and this system is on a mainframe written in Cobol. Is there any way using machine learning in which we can learn from the inputs and outputs the way the executables…
jcromanu
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5
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2 answers
What is the purpose of the batch size in neural networks?
Why is a batch size needed to update the weights of a neural network?
According to that Youtube Video from 3B1B, the weights are updated by calculating the error between expectation and outcome of the neural net. Based on that, the chain rule is…
MScott
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Many of the best probabilistic models represent probability distributions only implicitly
I am currently studying Deep Learning by Goodfellow, Bengio, and Courville. In chapter 5.1.2 The Performance Measure, P, the authors say the following:
The choice of performance measure may seem straightforward and objective, but it is often…
The Pointer
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What AI applications exist to solve sustainability issues?
The Sustainable Development Goals of the United Nations describe a normative framework which states what future development until 2030 should strive for. On a more abstract level a basic definition describes sustainable development as
development…
cknoll
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