Most Popular
1500 questions
5
votes
2 answers
What are the common pitfalls that we could face when training neural networks?
Apart from the vanishing or exploding gradient problems, what are other problems or pitfalls that we could face when training neural networks?
pjoter
- 51
- 1
5
votes
1 answer
What happens if the opponent doesn't play optimally in minimax?
I just read an article about the minimax algorithm. When you design the algorithm, you assume that your opponent is a perfect player, i.e. it plays optimally.
Let's consider the game of chess. What happens if the opponent plays irrationally or…
dato nefaridze
- 872
- 8
- 20
5
votes
2 answers
Are bandits considered an RL approach?
If a research paper uses multi-armed bandits (either in their standard or contextual form) to solve a particular task, can we say that they solved this task using a reinforcement learning approach? Or should we distinguish between the two and use…
user5093249
- 722
- 4
- 8
5
votes
3 answers
Is it possible to separately evolve a part of the population?
In a classic example of a genetic algorithm, you would have a population and a certain amount of simulation time to evaluate it and breeding. Then proceed to the next generation.
Is it possible, during the simulation process, to have an isolated and…
mikerson
- 53
- 2
5
votes
1 answer
Loss function for choosing a subset of objects
I'm trying to train a neural net to choose a subset from some list of objects.
The input is a list of objects $(a,b,c,d,e,f)$ and for each list of objects the label is a list composed of 0/1 - 1 for every object that is in the subset, for example…
Gilad Deutsch
- 649
- 5
- 12
5
votes
6 answers
What jobs cannot be automatized by AI in the future?
AI is progressing drastically, and imagine they tell you you're fired because a robot will take your place. What are some jobs that can never be automated?
bmwalide
- 399
- 2
- 6
5
votes
2 answers
Is it possible to guide a reinforcement learning algorithm?
I have just started to study reinforcement learning and, as far as I understand, existing algorithms search for the optimal solution/policy, but do not allow the possibility for the programmer to suggest a way to find the solution (to guide their…
Cristian M
- 249
- 2
- 6
5
votes
4 answers
How does size of the dataset depend on VC dimension of the hypothesis class?
This might be a little broad question, but I have been watching Caltech youtube videos on Machine Learning, and in this video prof. is trying to explain how we should interpret the VC dimension in terms of what it means in layman terms, and why do…
Stefan Radonjic
- 187
- 5
5
votes
1 answer
What is the calcium equivalent role in neural networks
I understand that neural networks model biological neurons. Each node in the network represents a neuron cell and the connections between nodes represent the connections between cells. As in nature, a neuron fires an electrical signal to connected…
k rey
- 163
- 4
5
votes
1 answer
What are some resources for coding some artificial intelligence techniques in the context of games?
I know the most basic rudimentary theory on AI, and I want to delve into actual practical coding with AI and machine learning. I already know a decent bit of coding in C++ and I'm learning Python syntax now.
I think I want to start implementing…
Tarun
- 53
- 4
5
votes
3 answers
Isn't a simulation a great model for model-based reinforcement learning?
Most reinforcement learning agents are trained in simulated environments. The goal is to maximize performance in (often) the same environment, preferably with a minimum amount of interactions. Having a good model of the environment allows to use…
Ray Walker
- 451
- 3
- 8
5
votes
2 answers
Why is it called back-propagation?
While looking at the mathematics of the back-propagation algorithm for a multi-layer perceptron, I noticed that in order to find the partial derivative of the cost function with respect to a weight (say $w$) from any of the hidden layers, we're just…
Skawang
- 153
- 4
5
votes
2 answers
Why do we need both the validation set and test set?
I know that this has been asked a hundred times before, however, I was not able to find a question (and an answer) which actually answered what I wanted to know, respectively, which explained it in a way I was able to understand. So, I'm trying to…
Golo Roden
- 173
- 5
5
votes
1 answer
How to add a dense layer after a 2d convolutional layer in a convolutional autoencoder?
I am trying to implement a convolutional autoencoder with a dense layer at the bottleneck to do some dimensional reduction. I have seen two approaches for this, which aren't particularly scalable. The first was to introduce 2 dense layers (one at…
Pavan Inguva
- 71
- 1
- 2
5
votes
3 answers
Are Convolutional Neural Networks better than existing image recognition libraries that don't use CNNs?
Are Convolutional Neural Networks summarily better than pattern recognition in all existing image processing libraries that don't use CNN's? Or are there still hard outstanding problems in image processing that seem to be beyond their capability?
dynrepsys
- 1,363
- 11
- 22