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1500 questions
5
votes
4 answers
Why isn't conditional probability sufficient to describe causality?
I read these comments from Judea Pearl saying we don't have causality, physical equations are symmetric, etc. But the conditional probability is clearly not symmetric and captures directed relationships.
How would Pearl respond to someone saying…
user3180
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5
votes
3 answers
Preventing bias by not providing irrelevant data
This seems like such a simple idea, but I've never heard anyone that has addressed it, and a quick Google revealed nothing, so here it goes.
The way I learned about machine learning is that it recognizes patterns in data, and not necessarily ones…
Levi Lesches
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5
votes
2 answers
In a neural network, by how much does the number of neurons typically vary from layer to layer?
In a neural network, by how much does the number of neurons typically vary from layer to layer?
Note that I am NOT asking how to find the optimal number of neurons per layer.
As a hardware design engineer with no practical experience programming…
Angela Johnson
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5
votes
1 answer
What are the benefits of using max-pooling in convolutional neural networks?
I am reading Francois Chollet's Deep learning with Python, and I came across a section about max-pooling that's really giving me trouble.
I am unable to copy-paste the content, so I've included screenshots of the paragraph that's troubling me.
I…
An Ignorant Wanderer
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1 answer
Can I train a neural network incrementally given new daily data?
I would like to know if it was possible to train a neural network on daily new data. Let me explain this more in detail. Let's say you have daily data from 2010 to 2019. You train your NN on all of it, but, from now on, every day in 2019 you get new…
neomatriciel
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5
votes
4 answers
Can we destroy an artificial general intelligence without its consent?
According to Wikipedia Artificial general intelligence(AGI)
Artificial general intelligence (AGI) is the intelligence of a
(hypothetical) machine that could successfully perform any
intellectual task that a human being can.
According to the…
Eka
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5
votes
1 answer
What approach should I take to model forecasting problem in machine learning?
I have a dataset which contains 4000k rows and 6 columns. The goal is to predict travel time demand of a taxi. I have read many articles regarding how to approach the problem. So, every writer tell his own way. The thing which I have concluded from…
Saeed Ahmad
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5
votes
1 answer
It is possible to solve a problem with continuous action spaces and no states with reinforcement learning?
I want to use Reinforcement Learning to optimize the distribution of energy for a peak shaving problem given by a thermodynamical simulation. However, I am not sure how to proceed as the action space is the only thing that really matters, in this…
FS93
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5
votes
1 answer
Understanding the equation of TD(0) in the paper "Learning to predict by the methods of temporal differences"
In the paper Learning to predict by the methods of temporal differences (p. 15), the weights in the temporal difference learning are updated as given by the equation
$$
\Delta w_t
= \alpha \left(P_{t+1} - P_t\right) \sum_{k=1}^{t}{\lambda^{t-k}…
Amanda
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5
votes
3 answers
Which function $(\hat{y} - y)^2$ or $(y - \hat{y})^2$ should I use to compute the gradient?
The MSE can be defined as $(\hat{y} - y)^2$, which should be equal to $(y - \hat{y})^2$, but I think their derivative is different, so I am confused of what derivative will I use for computing my gradient. Can someone explain for me what term to…
Jerico Bayod
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5
votes
1 answer
How to create a custom environment for reinforcement learning
I am a newbie in reinforcement learning working on a college project. The project is related to optimizing the hardware power. I am running proprietary software in Linux distribution (16.04). The goal is to use reinforcement learning and optimize…
NewToCoding
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5
votes
2 answers
Are filters fixed or learned?
No matter what I google or what paper I read, I can't find an answer to my question. In a deep convolutional neural network, let's say AlexNet (Krizhevsky, 2012), filters' weights are learned by means of back-prop.
But how are kernels themselves…
nvergontbij
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5
votes
2 answers
What is a simple game for validation of MCTS?
What is a simple turn-based game, that can be used to validate a Monte-Carlo Tree Search code and it's parameters?
Before applying it to problems where I do not have a possiblity to validate its moves for correctness, I would like to implement a…
allo
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5
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3 answers
How is neural architecture search performed?
I have come across something that IBM offers called neural architecture search. You feed it a data set and it outputs an initial neural architecture that you can train.
How is neural architecture search (NAS) performed? Do they use heuristics, or is…
Adam Geringer
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5
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1 answer
Are the ideas in the paper "Governance by Glass-Box: Implementing Transparent Moral Bounds for AI Behaviour" novel?
In the paper Governance by Glass-Box: Implementing Transparent Moral Bounds for AI Behaviour, the authors seem to be presenting a black box method of testing. Are these ideas really new? Weren't these ideas already proposed in Translating Values…
Kaspar
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