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1500 questions
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How do I combine models trained on different data to increase classification accuracy?
I have two trained models. One is using a LinearSVC algorithm and is trained on numerical data from medical examination from patients with diabetic retinopathy. The second one is a neural network trained on images of retina scans from patients with…
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Why does a Lipschitz continuous discriminator in GANs assure statistical boundedness?
I have been reading the paper which introduced spectral normalization in GANs.
At some point the paper mentions the following:
The machine learning community has been pointing out recently that the
function space from which the discriminators are…
MattSt
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Why is the Jensen-Shannon divergence preferred over the KL divergence in measuring the performance of a generative network?
I have read articles on how Jensen-Shannon divergence is preferred over Kullback-Leibler in measuring how good a distribution mapping is learned in a generative network because of the fact that JS-divergence better measures distribution similarity…
ashenoy
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How to create an AI to solve a word search?
This at first sounds ridiculous. Of course there is an easy way to write a program to solve a wordsearch.
But what I would like to do is write a program that solves a word-search like a human.
That is, use or invent different strategies. e.g.…
zooby
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Are deep learning models more prone to overfitting than machine learning ones?
In my opinion, deep learning algorithms and models (that is, multi-layer neural networks) are more sensitive to overfitting than machine learning algorithms and models (such as the SVM, random forest, perceptron, Markov models, etc.). They are…
jennifer ruurs
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5
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What are methods human actors use to imitate robots?
Robot technology is usually thought from an engineering perspective. A human programmer writes a software this executed in a robot who is doing a task.
But what would happen, if the project is started with the opposite goal? The idea is, that the…
user11571
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Given enough computational resources, do we currently have any algorithms which could achieve AI?
Hypothetically, assume that you have access to infinite computing power. Do we have designs for any brute-force algorithms that can find an AI capable of passing traditional tests (e.g. Turing, Chinese Room, MIST, etc.)?
Tim Atkinson
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Which part of "Perceptrons: An Introduction to Computational Geometry" tells that a perceptron cannot solve the XOR problem?
In the book "Perceptrons: An Introduction to Computational Geometry" by Minsky and Papert (1969), which part of this book tells that a single-layer perceptron could not solve the XOR problem?
I have been already scanned it, but I did not find the…
rimbaerl
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Do models train better if the labelling information is more specific (or dense)?
I'm working on a project where there is a limited dataset of videos (about 200). We want to train a model that can detect a single class in the videos. That class can be of multiple different types of shapes (thin wire, a huge area of the screen,…
NateW
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Is it possible to vectorise a CNN?
I am trying to write a CNN from scratch and am wondering if it is possible to vectorize the convolution step.
For example, if I had a dataset of 500 RGB images of size 32x32x3, and wanted the first convolutional layer to have 64 filters, how would I…
FeedMeInformation
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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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5
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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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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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