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Results tagged with machine-learning
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user 77374
Questions about computer algorithms that automatically discover patterns in data and make good decisions based on them.
1
vote
Machine Learning: if test, validation errors are same, the model with lower train loss is be...
Though usually the test error is your primary goal, I can imagine some specific cases when the train error also matters. One possible example: training set has much more 'hard' inputs than the test se …
- 640
1
vote
How to calculate the total error from an arbitrary hidden layer in a neural network back pro...
The short answer is yes, $\frac{\partial E_{total}}{\partial w_1} = \frac{\partial E_{j_1}}{\partial w_1} + \frac{\partial E_{j_2}}{\partial w_1}$.
The long answer. The key formula is the chain rule, …
- 640
5
votes
Accepted
Is genetic programming relevant today?
The research is well in progress, though not so much talked about in comparison to machine learning, deep learning in particular.
Genetic algorithms are applied in particular research areas (example …
- 640
3
votes
What are the drawbacks of fully-convolutional neural networks?
All-convolutional network is a great idea exactly because it has much more advantages than disadvantages. Most of modern convolutional networks are designed to use CONV for everything. If you are focu …
- 640
3
votes
Some questions on kernels and Reinforcement Learning
Is that valid? My question is how can I distinguish between a valid kernel and a nonvalid kernel if I'm given a kernel in the test?
Yes, it will be a valid kernel for all practical purposes, beca …
- 640
1
vote
What determines the number of inputs and outputs when initialising weights in a convolutiona...
The question is about basic principles of Convolutional Neural Networks, specifically how the layers are organized (it's best explained here, in fact I highly recommend to complete the whole CS231n co …
- 640
4
votes
Accepted
What is the role of Numerical Gradient Computation in Backpropagation algorithm?
The purpose is pure educational. Students that jump straight to mid- or high-level libraries like tensorflow, keras, theano, etc don't have to compute the gradients themselves. On the one hand, it sav …
- 640
1
vote
How to figure out whether two texts refer to the same object or event
This is a document clusterization problem. A general solution is to define some sort of distance between documents and apply a standard clusterization algorithm, such as k-means or expectation maximiz …
- 640
4
votes
How many possible policies in a Markov Decision Process?
Looks like you are a bit confused by the notion of MDP policy. There's a detailed discussion with lots of examples in this question.
A policy is any possible strategy in a given environment. Example: …
- 640
1
vote
Google's Deep Dreamer
So far nothing's been said about technical details of DeepDream. I'll fill the blank.
The procedure is the following: pick some layer from the network (usually a convolutional layer), pass the starti …
- 640
7
votes
Google DeepDream Elaborated
The idea of DeepDream is this: pick some layer from the network (usually a convolutional layer), pass the starting image through the network to extract features at the chosen layer, set the gradient a …
- 640