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1500 questions
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Has machine learning been combined with logical reasoning (for example, PROLOG)?
There are mainly two different areas of AI at the moment. There is the "learning from experience" based approach of neural networks. And there is the "higher logical reasoning" approach, with languages like LISP and PROLOG.
Has there been much…
zooby
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What is the meaning of the square brackets in ant colony optimization?
I'm studying the paper "Minimizing Total Tardiness on a Single Machine Using Ant Colony Optimization" which has proposed to use Ant colony optimization to SMTWTP.
According to this paper:
Each artificial ant iteratively and independently decides…
Pablo
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Why do small datasets require more samples, while big datasets require fewer samples in negative sampling?
In the deep learning specialization course by Andrew Ng, in the video Sequence Models (minute 4:13), he says that in negative sampling we have to choose a sample of words from the corpus to train rather than choosing the whole corpus. But he said…
A_the_kunal
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How can artificial intelligence (including deep learning algorithms) find suspicious patterns in the body’s biochemistry?
It has been suggested that machine learning algorithms (also Watson) can help with finding disease in patient images and optimize scans. Also that deep learning algorithms show promise for every type of digital imaging.
How does exactly deep…
kenorb
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5
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1 answer
Should the policy parameters be updated at each time step or at the end of the episode in REINFORCE?
REINFORCE is a Monte Carlo policy gradient algorithm, which updates weights (parameters) of policy network by generating episodes. Here's a pseudo-code from Sutton's book (which is same as the equation in Silver's RL note):
When I try to implement…
Seewoo Lee
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5
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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
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
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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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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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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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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
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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
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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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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
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1 answer
How can we conclude that an optimization algorithm is better than another one
When we test a new optimization algorithm, what the process that we need to do?For example, do we need to run the algorithm several times, and pick a best performance,i.e., in terms of accuracy, f1 score .etc, and do the same for an old optimization…
user29902
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