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1500 questions
6
votes
1 answer
How to avoid falling into the "local minima" trap?
How do I avoid my gradient descent algorithm into falling into the "local minima" trap while backpropogating on my neural network?
Are there any methods which help me avoid it?
Dawny33
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6
votes
1 answer
Has any research been done on DNN Music?
DNNs are typically used to classify things (of course) but can we let them go wild with sounds and then tell them if we think it sounds good or not? I'd like to think after a training class has been made (perhaps comparing the output to an existing…
Andrew
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6
votes
1 answer
Why can't neural networks learn functions outside of the specified domains?
I understand that neural nets are fundamentally interpolative tools. Meaning, given a training dataset, a well trained neural net can approximate values within the domain of the training dataset. However, we are unsure about their behavior once we…
Robot0110
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6
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1 answer
Suicide Predictor and Locator
Suicide is on the increase in my country and most victims tend to leave early traces from text messages, social media accounts, search engine queries. So I came up with the idea to develop an AI system with the following features:
Ability to read…
Hadassah Airekun
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6
votes
1 answer
How important is true randomness in AI designs?
How important is true (non-pseudo) randomness in Artificial Intelligence designs? Is there any chance that pseudo-randomness could be a barrier to more successful designs?
dynrepsys
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6
votes
1 answer
Can a vanilla neural network theoretically achieve the same performance as CNN?
I perfectly understand that CNN takes into account the local dependency of each pixel to the nearby pixels. In addition, CNNs are spatially invariant which means that they are able to detect the same feature anywhere in the image. These qualities…
Robot0110
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6
votes
2 answers
Can neuroevolution be combined with gradient descent?
Is there any precedent for using a neuroevolution algorithm, like NEAT, as a way of getting to an initialization of weights for a network that can then be fine-tuned with gradient descent and back-propagation?
I wonder if this may be a faster way…
benbyford
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6
votes
3 answers
In sequence-to-sequence, why is the output of the decoder used as its input?
The basic seq-2-seq model consists of 2 parts: a recurrent encoder that compresses a sequence to a vector and decoder that unrolls the vector into the output sequence:
Why is the output, w, x, y, z of the decoder used as its input? Shouldn't the…
user8426627
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6
votes
1 answer
Is AI capable to replace pilots entirely on the commercial flights?
Since we've self-driving cars already, would we have self-flying commercial flights in the near future? Basically the AI which can do take off, flying, landing and parking.
kenorb
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6
votes
2 answers
What are the most compact Real Time-Strategy Games?
There was a recent informal question on chat about RTS games suitable for AI benchmarks, and I thought it would be useful to ask a question about them in relation to AI research.
Compact is defined as the fewest mechanics, elements, and smallest…
DukeZhou
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6
votes
4 answers
Is it possible for a neural network to be used to compress data?
When training a neural network, we often run into the issue of overfitting.
However, is it possible to put overfitting to use? Basically, my idea is, instead of storing a large dataset in a database, you can just train a neural network on the entire…
Bryan Tan
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6
votes
1 answer
How do big companies, like Facebook, model individuals and their interaction?
As a layman in AI, I want to get an idea of how big data players, like Facebook, model individuals (of which they have so many data).
There are two scenarios I can imagine:
Neural networks build clusters of individuals by pure and "unconscious" big…
Hans-Peter Stricker
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6
votes
2 answers
Is there a machine learning algorithm to find similar sales patterns?
I have a dataset as follows
(and the table extends to include an extra 146 columns for companies 4-149)
Is there an algorithm I could use effectively to find similar patterns in sales from the other companies when compared to my company?
I thought…
Anonymous
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6
votes
1 answer
What is local consistency in constraint satisfaction problems?
In the Constraint Propagation in CSP, it is often stated that pre-processing can solve the whole problem, so no search is required at all. And the key idea is local consistency. What does this actually mean?
Lexi
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6
votes
2 answers
How is parallelism implemented in RL algorithms like PPO?
There are multiple ways to implement parallelism in reinforcement learning. One is to use parallel workers running in their own environments to collect data in parallel, instead of using replay memory buffers (this is how A3C works, for…
alex vdk
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