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1500 questions
5
votes
2 answers
Which linear algebra book should I read to understand vectorized operations?
I am reading Goodfellow's book about neural networks, but I am stuck in the mathematical calculus of the back-propagation algorithm. I understood the principle, and some Youtube videos explaining this algorithm shown step-by-step, but now I would…
lolveley
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5
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1 answer
What could be the cause of the drop in the reward in A3C?
The mean episodic reward is generally increasing, but it has spontaneous drops, and I'm not sure of their cause.
The problem has a sparse reward, batch size=2000, entropy_coefficient=0.1, other hyper-parameters are pretty standard.
Has anyone seen…
Gabizon
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5
votes
1 answer
How many weights does the max-pooling layer have?
How many weights does the max-pooling layer have?
For example, if there are 10 inputs, a pooling filter of size 2, stride 2, how many weights, including bias, does a max-pooling layer have?
Tibby
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5
votes
1 answer
What is the relationship between fuzzy logic and objective bayesian probability?
I understand fuzzy logic is a variant of formal logic where, instead of just 0 or 1, a given sentence may have a truth value in the [0..1] interval. Also, I understand that logical probability (objective bayesian) understands probability as an…
olinarr
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5
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1 answer
How can I avoid overfitting when doing parameter tuning?
I very often applied a grid search to tune the parameters of my supervised model. I have the feeling that parameter tuning will eventually (very often) lead to overfitting? Is this crazy to say?
Is there a way that we can apply grid search in such a…
jennifer ruurs
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5
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2 answers
How does text classification reduce manpower costs?
(I apologize for the title being too broad and the question being not 'technical')
Suppose that my task is to label news articles. This means that given a news article, I am supposed to classify which category that news belong to. Eg, 'Ronaldo…
Air Christmas
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votes
1 answer
How do we compute the target value when the agent ends up in the terminal state?
I am working on a deep reinforcement learning problem. Throughout the episode, there is a small positive and negative reward for good or bad decisions. In the end, there is a huge reward for the completion of the episode. So, this reward function is…
pranav
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votes
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Why is my implementation of Q-learning not converging to the right values in the FrozenLake environment?
I am trying to learn tabular Q learning by using a table of states and actions (i.e. no neural networks). I was trying it out on the FrozenLake environment. It's a very simple environment, where the task is to reach a G starting from a source S…
abkds
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5
votes
2 answers
Is the gradient at a layer independent of the activations of the previous layers?
Is the gradient at a layer (of a feed-forward neural network) independent of the activations of the previous layers?
I read this in a paper titled Mean Field Residual Networks: On the Edge of Chaos (2017). I am not sure how far this is true, because…
Snehal Reddy
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5
votes
1 answer
What are examples of optimization problems that can be solved using genetic algorithms?
I'm trying to learn how genetic algorithms can solve optimization problems. I have already learned how genetic algorithms can solve the knapsack, TSP and set cover problems. I'm looking for some other similar optimization problems, but I have not…
Pablo
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5
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1 answer
Is the agent aware of a possible different set of actions for each state?
I have a use case where the set of actions is different for different states. Is the agent aware of what actions are valid for each state, or is the agent only aware of the entire action space (in which case I guess the environment needs to discard…
Francis Chang
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5
votes
1 answer
Why evolutionary training of neural networks is not popular?
Evolutionary algorithms are mentioned in some sources as a method to train a neural network (finding weights, not hyperparameters). However, I have not heard about one practical application of such an idea yet.
My question is, why is that? What are…
GKozinski
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votes
2 answers
Can ML be used to curve fit data based on dataset of example fits?
Say I have x,y data connected by a function with some additional parameters (a,b,c):
$$ y = f(x ; a, b, c) $$
Now given a set of data points (x and y) I want to determine a,b,c. If I know the model for $f$, this is a simple curve fitting problem.…
argentum2f
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5
votes
2 answers
What is the difference between abstract, autonomous and virtual intelligent agents?
On Wikipedia, we can read about different type of intelligent agents:
abstract intelligent agents (AIA),
autonomous intelligent agents,
virtual intelligent agent (IVA), which I've found on other websites, e.g. this one.
What are the differences…
kenorb
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5
votes
1 answer
Is it possible to fool a facial recognition algorithm?
Assuming we're dealing with an artificial neural network (e.g. a ConvNet), which was trained by a large dataset of human faces.
Are there any known issues or challenges where facial recognition would fail? I'm not talking about covering half of the…
kenorb
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