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1500 questions
6
votes
1 answer
How to classify human actions?
I'm quite new to machine learning (I followed the Coursera course of Andrew Ng and now starting deeplearning.ai courses).
I want to classify human actions real-time like:
Left-arm bended
Arm above shoulder
...
I first did some research for…
user1007522
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6
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2 answers
How to understand the concept of self-supervised learning in AI?
I am new to self-supervised learning and it all seems a little magical at the moment.
The only way I can get an intuitive understanding is to assume that, for real-world problems, features are still embedded at a per-object level.
For example, to…
user3546025
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6
votes
1 answer
Interesting examples of discrete stochastic games
SGs are a generalization of MDPs to multiple agents. Like this previous question on MDPs, are there any interesting examples of zero-sum, discrete SGs—preferably with small state and action spaces? I'm hoping to use such examples as benchmarks, but…
user76284
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6
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1 answer
Why was ELIZA able to induce "delusional thinking"?
From Eliza to A.L.I.C.E.:
Weizenbaum tells us that he was shocked by the experience of releasing ELIZA (also known as "Doctor") to the nontechnical staff at the MIT AI Lab. Secretaries and nontechnical administrative staff thought the machine was a…
Left SE On 10_6_19
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6
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Why cannot an AI agent adjust the reward function directly?
In standard Reinforcement Learning the reward function is specified by an AI designer and is external to the AI agent. The agent attempts to find a behaviour that collects higher cumulative discounted reward. In Evolutionary Reinforcement Learning…
rodan
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6
votes
2 answers
Does using the softmax function in Q learning not defeat the purpose of Q learning?
It is my understanding that, in Q-learning, you are trying to mimic the optimal $Q$ function $Q*$, where $Q*$ is a measure of the predicted reward received from taking action $a$ at state $s$ so that the reward is maximised.
I understand for this to…
Recessive
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To deal with infinite loops, should I do a deeper search of the best moves with the same value, in alpha-beta pruning?
I have implemented minimax with alpha-beta pruning to play checkers. As my value heuristic, I am using only the summation of material value on the board regardless of the position.
My main issue lays in actually finishing games. A search with depth…
TurbulentWinds
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6
votes
1 answer
What is the relationship between robustness and adversarial machine learning?
I have been reading a lot of articles on adversarial machine learning and there are mentions of "best practices for robust machine learning".
A specific example of this would be when there are references to "loss of efficient robust estimation in…
boomselector
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Are there any easy ways to create annotated training images for object detection?
For the purposes of object detection, are there any easy ways to create annotated training images? For example, if we have $10,000$ images and want to draw bounding boxes on 2 objects for each image, do we have to physically draw those boxes? Is…
James
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6
votes
1 answer
How to deal with images of different sizes, which need to be passed to a model of fixed input size, without losing details and spatial information?
I have the following problem while using convolutional neural networks to detect forgeries:
Resizing the image to fit the required input size may not be a good way because the forgery detection largely relies on the details of images, for example,…
Ivan Zhu
- 61
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6
votes
1 answer
How do artificial neural networks store data compared to biological neural networks?
Do scientists know by what mechanism biological brains/biological neural networks store data?
I only have a vague notion that we store data in our brains by altering synapses.
I also would love a decent description of how a vanilla artificial neural…
Conor
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6
votes
4 answers
Is k-fold cross-validation more effective than splitting the dataset into training and test datasets to prevent overfitting?
I want to prevent my model from overfitting. I think that k-fold cross-validation (because it is doing this each time with different datasets) may be more effective than splitting the dataset into training and test datasets to prevent overfitting,…
jennifer ruurs
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3 answers
What is a "surrogate model"?
In the following paragraph from the book Automated Machine Learning: Methods, Systems, Challenges (by Frank Hutter et al.)
In this section we first give a brief introduction to Bayesian optimization, present alternative surrogate models used in it,…
yousef yegane
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6
votes
3 answers
What evaluation metric are used for sequence-to-sequence prediction problems?
I am solving many sequence-to-sequence prediction problems using RNN/LSTM.
What type of evaluation metrics can be used for sequence prediction problems?
One metric is the mean squared error (MSE) that we can give as a parameter during the training…
Asif Khan
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6
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2 answers
Are perfect and imperfect information games modelled as fully and partially observable environments, respectively?
In perfect information games, the agent can see all the moves performed in the past. Besides, it can observe the next action that will be put into practice by the opponent.
In this case, can we say that perfect information games are actually a…
Goktug
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