### Predicting next number in a sequence

I’ve been dabbling with Machine Learning and Neural Networks (namely resnet50) for a few months now, mostly doing image recognition. I am currently trying to make a program that, given a string of numbers as input, can predict the next number in this sequence. For example: Input: 1:2:3:4 Output: 5 I read something that said…

### How does the update rule for the one-step actor-critic method work?

Can you please elucidate the math behind the update rule for the critic? I’ve seen in other places that just a squared distance of $R + \hat{v}(S’, w) – \hat{v}(S,w)$ is used, but Sutton suggests an update rule (and the math behind) that is beyond my understanding? Also, why do we need $I$?

### How does the update rule for the one-step actor-critic method work?

Can you please elucidate the math behind the update rule for the critic? I’ve seen in other places that just a squared distance of $R + \hat{v}(S’, w) – \hat{v}(S,w)$ is used, but Sutton suggests an update rule (and the math behind) that is beyond my understanding? Also, why do we need $I$?

### How does the update rule for the one-step actor-critic method work?

Can you please elucidate the math behind the update rule for the critic? I’ve seen in other places that just a squared distance of $R + \hat{v}(S’, w) – \hat{v}(S,w)$ is used, but Sutton suggests an update rule (and the math behind) that is beyond my understanding? Also, why do we need $I$?

### What is “Computational Linguistics”?

It’s not clear to me whether or not someone whose work aims to improve an NLP system may be called a “Computational Linguist” even when she/he doesn’t modify the algorithm directly by coding. Let’s consider the following activities: Annotation for Machine Learning: analysis of Morphology, Syntax, POS tagging Annotation, analysis, and annotation of entities (NER)…

### Why do CNN’s sometimes make highly confident mistakes, and how can one combat this problem?

I trained a simple CNN on the MNIST database of handwritten digits to 99% accuracy. I’m feeding in a bunch of handwritten digits, and non-digits from a document. I want the CNN to report errors, so I set a threshold of 90% certainty below which my algorithm assumes that what it’s looking at is not…

### Why do CNN’s sometimes make highly confident mistakes, and how can one combat this problem?

I trained a simple CNN on the MNIST database of handwritten digits to 99% accuracy. I’m feeding in a bunch of handwritten digits, and non-digits from a document. I want the CNN to report errors, so I set a threshold of 90% certainty below which my algorithm assumes that what it’s looking at is not…

### Why do CNN’s sometimes make highly confident mistakes, and how can one combat this problem?

I trained a simple CNN on the MNIST database of handwritten digits to 99% accuracy. I’m feeding in a bunch of handwritten digits, and non-digits from a document. I want the CNN to report errors, so I set a threshold of 90% certainty below which my algorithm assumes that what it’s looking at is not…

### Deep Belief Networks vs Convolutional Neural Networks performance on non-Image Classification Tasks

In the paper Improved Classification Based on Deep Belief Networks, the authors have stated that for better classification, generative models are used to initialize the model and model features before training a classifier. Typically they are needed to solve separate unsupervised and supervised learning problems. Generative restricted Boltzmann machines and deep belief networks are widely…

### Why is multi-agent deep deterministic policy gradient (MADDPG) running slowly and taking only 22% from the GPU?

I already asked this question on StackOverflow where I need to run the distributed multi-agent cooperation algorithm based on MADDPG with prioritized batch data code with increasing the number of agents to be 12 agents, but it takes a lot of time to train for 3500 episodes. I have tried different setting but nothing is…