Most Popular
1500 questions
5
votes
3 answers
What is an adversarial attack?
I'm reading this really interesting article CycleGAN, a Master of Steganography. I understand everything up until this paragraph:
we may view the CycleGAN training procedure as continually mounting an adversarial attack on $G$, by optimizing a…
Cyclist
- 51
- 1
5
votes
1 answer
Is it possible to combine two neural networks trained on different tasks into one that knows both tasks?
I'm relatively new to artificial intelligence and neural networks.
Let's say I have two different fully trained neural networks. The first one is trained for mathematical addition and the second one on mathematical multiplication. Now, I want to…
vP3nguin
- 153
- 5
5
votes
2 answers
Is pooling a kind of dropout?
If I got well the idea of dropout, it allows improving the sparsity of the information that comes from one layer to another by setting some weights to zero.
On the other hand, pooling, let's say max-pooling, takes the maximum value in a…
nsaura
- 258
- 2
- 7
5
votes
2 answers
How does the NEAT speciation algorithm work?
I've been reading up on how NEAT (Neuro Evolution of Augmenting Topologies) works and I've got the main idea of it, but one thing that's been bothering me is how you split the different networks into species. I've gone through the algorithm but it…
Aguy
- 65
- 1
- 7
5
votes
2 answers
Why is the Chinese Room argument such a big deal?
I've been re-reading the Wikipedia article on the Chinese Room argument and I'm... actually quite unimpressed by it. It seems to me to be largely a semantic issue involving the conflation of various meanings of the word "understand". Of course,…
wizzwizz4
- 225
- 1
- 12
5
votes
2 answers
When should I use simulated annealing as opposed to a genetic algorithm?
What kind of problems is simulated annealing better suited for compared to genetic algorithms?
From my experience, genetic algorithms seem to perform better than simulated annealing for most problems.
Abbas Ali
- 576
- 4
- 10
- 17
5
votes
1 answer
How do I show that uniform-cost search is a special case of A*?
How do I show that uniform-cost search is a special case of A*? How do I prove this?
dua fatima
- 323
- 1
- 3
- 11
5
votes
4 answers
What is the difference between "mutation" and "crossover"?
In the context of evolutionary computation, in particular genetic algorithms, there are two stochastic operations "mutation" and "crossover". What are the differences between them?
Abbas Ali
- 576
- 4
- 10
- 17
5
votes
1 answer
How is simulated annealing better than hill climbing methods?
In hill climbing methods, at each step, the current solution is replaced with the best neighbour (that is, the neighbour with highest/smallest value). In simulated annealing, "downhills" moves are allowed.
What are the advantages of simulated…
Huma Qaseem
- 199
- 1
- 3
- 12
5
votes
3 answers
What is the actual learning algorithm: back-propagation or gradient descent?
What is the actual learning algorithm: back-propagation or gradient descent (or, in general, the optimization algorithm)?
I am reading through chapter 8 of Parallel Distributed Processing hand book and the title of the chapter is "Learning internal…
Sreedhar Veluri
- 100
- 6
5
votes
1 answer
What are the differences between uniform-cost search and greedy best-first search?
What are the differences between the uniform-cost search (UCS) and greedy best-first search (GBFS) algorithms? How would you convert a UCS into a GBFS?
Abbas Ali
- 576
- 4
- 10
- 17
5
votes
7 answers
What are the most instructive movies about artificial intelligence?
The field of AI has expanded profoundly in recent years, as has public awareness and interest. This includes the arts, where fiction about AI has been popular since at least Isaac Asimov. Films on various subjects can be good teaching aids,…
Marosh Fatima
- 375
- 1
- 3
- 10
5
votes
1 answer
How do I predict if it is rainy or not?
I'm building a weather station, where I'm sensing temperature, humidity, air pressure, brightness, $CO_2$, but I don't have a raindrop sensor.
Is it possible to create an AI which can say if it's raining or not, with the help of the given data…
Ribisl
- 51
- 4
5
votes
1 answer
Deep Q-Learning: why don't we use mini-batches during experience reply?
In examples and tutorial about DQN, I've often noticed that during the experience replay (training) phase people tend to use stochastic gradient descent / online learning. (e.g. link1, link2)
# Sample minibatch from the memory
minibatch =…
ent
- 53
- 4
5
votes
2 answers
How much can the addition of new features improve the performance?
How much can the addition of new features improve the performance of the model during the optimization process?
Let's say I have a total of 10 features. Suppose I start the optimisation process using only 3 features.
Can the addition of the 7…
Miko Diko
- 177
- 1
- 2