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1500 questions
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What is the difference between the prediction and control problems in the context of Reinforcement Learning?
What is the difference between the prediction (value estimation) and control problems in reinforcement learning?
Are there scenarios in RL where the problem cannot be distinctly categorised into the aforementioned problems and is a mixture of the…
user9947
8
votes
2 answers
What is the point of using 1D and 2D convolutions with a kernel size of 1 and 1x1 respectively?
I understand the gist of what convolutional neural networks do and what they are used for, but I still wrestle a bit with how they function on a conceptual level. For example, I get that filters with kernel size greater than 1 are used as feature…
Arcturai
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8
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Is the AI Effect caused by bad tests of intelligence?
According to Wikipedia...
The AI effect occurs when onlookers discount the behavior of an artificial intelligence program by arguing that it is not real intelligence.
Pamela McCorduck writes: "It's part of the history of the field of artificial…
Left SE On 10_6_19
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8
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2 answers
What is the proof that policy evaluation converges to the optimal solution?
Although I know how the algorithm of iterative policy evaluation using dynamic programming works, I am having a hard time realizing how it actually converges.
It appeals to intuition that, with each iteration, we get a better and better…
SAGALPREET SINGH
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8
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2 answers
Is anybody still researching GOFAI?
A lot of textbooks and introductory lectures typically split AI into connectionism and GOFAI (Good Old Fashioned AI). From a purely technical perspective, it seems that connectionism has grown into machine learning and data science, while nobody…
Alex S King
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8
votes
2 answers
What are some online courses for deep reinforcement learning?
What are some (good) online courses for deep reinforcement learning?
I would like the course to be both programming and theoretical. I really liked David Silver's course, but the course dates from 2015. It doesn't really teach deep Q-learning at…
J.Doe
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8
votes
2 answers
Are there local search algorithms that make use of memory to give better solutions?
I have been studying local search algorithms such as greedy hill-climbing, stochastic hill-climbing, simulated annealing, etc. I have noticed that most of these methods take up very little memory as compared to systematic search techniques.
Are…
quantumcoder
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8
votes
2 answers
How can I solve the zero subset sum problem with hill climbing?
I want to solve the zero subset sum problem with the hill-climbing algorithm, but I am not sure I found a good state space for this.
Here is the problem: consider we have a set of numbers and we want to find a subset of this set such that the sum of…
K.N
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8
votes
2 answers
How big artificial neural networks can we run now if our total energy budget for computation is equivalent to the human brain energy budget?
How big artificial neural networks can we run now (either with full train-backprop cycle or just evaluating network outputs) if our total energy budget for computation is equivalent to the human brain energy budget (12.6 watts)?
Let assume one cycle…
liori
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8
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What are the differences between transfer learning and meta learning?
What are the differences between meta-learning and transfer learning?
I have read 2 articles on Quora and TowardDataScience.
Meta learning is a part of machine learning theory in which some
algorithms are applied on meta data about the case to…
Long
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8
votes
6 answers
What event would confirm that we have implemented an AGI system?
I was listening to a podcast on the topic of AGI and a guest made an argument that if strong music generation were to happen, it would be a sign of "true" intelligence in machines because of how much creative capability creating music requires (even…
Landon G
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8
votes
1 answer
What is the difference between LSTM and RNN?
What is the difference between LSTM and RNN? I know that RNN is a layer used in neural networks, but what exactly is an LSTM? Is it also a layer with the same characteristics?
Mao76
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8
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How does the generator in GAN's work?
After reading a lot of articles (for instance, this one - https://developers.google.com/machine-learning/gan/generator), I've been wondering: how does the generator in GAN's work?
What is the input to the generator? What is the meaning behind "input…
Shir K
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8
votes
2 answers
Effect of batch size and number of GPUs on model accuracy
I have a data set that was split using a fixed random seed and I am going to use 80% of the data for training and the rest for validation.
Here are my GPU and batch size configurations
use 64 batch size with one GTX 1080Ti
use 128 batch size with…
bit_scientist
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8
votes
1 answer
Do all neurons in a layer have the same activation function?
I'm new to machine learning (so excuse my nomenclature), and not being a python developer, I decided to jump in at the deep (no pun intended) end writing my own framework in C++.
In my current design, I have given each neuron/cell the possibility to…
lfgtm
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