# Tag Info

Accepted

### What is Temperature in LSTM (and neural networks generally)?

Temperature is a hyperparameter of LSTMs (and neural networks generally) used to control the randomness of predictions by scaling the logits before applying softmax. For example, in TensorFlow’s ...
• 945

### Why can't we say that a Neural Network is a NP problem solver?

SGD is an algorithm, not a problem. It is not NP-complete or NP-hard. SGD is one approach to an optimization problem. Some optimization problems are NP-hard; some are not. All of your deductions ...
• 143k
Accepted

### Evolving artificial neural networks for solving NP problems

No. This direction is unlikely to be useful, for two reasons: Most computer scientists believe that P $\ne$ NP. Assuming P $\ne$ NP, this means there does not exist any polynomial-time algorithm to ...
• 143k
Accepted

### what is difference between multilayer perceptron and multilayer neural network?

A perceptron is always feedforward, that is, all the arrows are going in the direction of the output. Neural networks in general might have loops, and if so, are often called recurrent networks. A ...
• 13.3k

### What is the difference between a Neural Network, a Deep Learning System and a Deep Belief Network?

Artificial neural networks is a class of algorithms that include a lot of different kinds of algorithms based on graphs, so I won't detail here beyond what you asked because there's too much to say, ...
• 346
Accepted

### Should activation function be monotonic in neural networks?

During the training phase, backpropagation informs each neuron how much it should influence each neuron in the next layer. If the activation function isn't monotonic then increasing the neuron's ...
• 7,863

### Evolving artificial neural networks for solving NP problems

It seems other answers while informative/ helpful are not actually understanding your question exactly and are reading a little too much into it. You didn't ask if neural networks would outperform ...
• 10.8k

### Why can't we say that a Neural Network is a NP problem solver?

Let me start by briefly reviewing the kind of problems under discussion: Problems in P: These are decision problems (where the answer is Yes or No), optimization problems (where the answer is an ...
• 270k