I am understanding the Bellman equation for updating the Q Table values. The concept of initially update the value is clear to me. What is unclear is the subsequent updates to the value. Is the value replaced with each episode? It doesn’t seem like this would learn from the past. Maybe average the value from…

### How are small scale features generated in an Inverse Graphics Networks?

This post refers to Fig. 1 of a paper by Microsoft on their Deep Convolutional Inverse Graphics Network: https://www.microsoft.com/en-us/research/wp-content/uploads/2016/11/kwkt_nips2015.pdf Having read the paper, I understand in general terms how the network functions. However, one detail has been bothering me: how does the network decoder (or “Renderer”) generate small scale features in the correct location as…

### Can we calculate mean recall and precision

I’m evaluating the accuracy in detecting objects for my image data set using three deep learning algorithms. I have selected a sample of 30 images. To measure the accuracy, I manually count the number of objects in each image and then calculate recall and precision values for three algorithms. Following is a sample: Finally to…

### Can we calculate mean recall and precision

I’m evaluating the accuracy in detecting objects for my image data set using three deep learning algorithms. I have selected a sample of 30 images. To measure the accuracy, I manually count the number of objects in each image and then calculate recall and precision values for three algorithms. Following is a sample: Finally to…

### Can we calculate mean recall and precision

I’m evaluating the accuracy in detecting objects for my image data set using three deep learning algorithms. I have selected a sample of 30 images. To measure the accuracy, I manually count the number of objects in each image and then calculate recall and precision values for three algorithms. Following is a sample: Finally to…

### I can train with a set of any size using the NN (mlp) , but the test-set always yields the bad evaluation results. Any solution?

The data that I can provide for learning is pseudo-random, and it just happened that I can train the Neural Nets (classical Multilayer perceptron) with any size as an input. The error while training is very low. However, as soon as I test it with a test-set, I get very bad results (Correlation coefficient is…

### I can train with a set of any size using the NN (mlp) , but the test-set always yields the bad evaluation results. Any solution?

The data that I can provide for learning is pseudo-random, and it just happened that I can train the Neural Nets (classical Multilayer perceptron) with any size as an input. The error while training is very low. However, as soon as I test it with a test-set, I get very bad results (Correlation coefficient is…

### How to back propagate for implementation of Sequence-to-Sequence with Multi Decoders

I am proposing a modified version of Sequence-to-Sequence model with dual decoders. The problem that I am trying to solve is Neural Machine Translation into two languages at once. This is the simplified illustration for the model. /–> Decoder 1 -> Language Output 1 Language Input -> Encoder -| \–> Decoder 2 -> Language Output…

### Deduce properties of the loss functions from the training loss curves

I have two convex, smooth loss functions to minimise. During the training (a very simple model) using batch SGD (with tuned optimal learning rate for each loss function), I observe that the (log) loss curve of the loss 2 converges much faster and is much more smooth than that of the loss 2, as shown…

### How can a system recognize if two input texts have same meaning?

Can you please let me know how to compare two inputted strings that if they have same meaning ? Example: String I: Wikipedia provide good information. String II: Wikipedia is good source of information. Please tell me how can i recognize if both strings have same meaning or logical meaning. Thank You