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5 views

How to train FFNN with Q-learning?

I know that in any NN architecture, the input data are states, and at the output layer Q-functionality of each action. Tell me please, how to adjust all weights in this case?
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0answers
7 views

Efficient implementation of seperable convolution in tensorflow

It seems like the native implementation of separable convolution in tensorflow is not efficient. https://github.com/tensorflow/tensorflow/issues/12940 Is anyone aware how can we get an efficient ...
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1answer
17 views

Why there's so much search for Python professionals in AI?

Even with ample knowledge about the low computational performance that Python has, and even though it is an interpreted language that is not recommended for real-time applications, it is the ...
2
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0answers
14 views

Autoencoder network for feature selection not converging

I am training an undercomplete autoencoder network for feature selection. I am using one hidden layer in the encoder and decoder networks each. The ELU activation function is used for each layer. For ...
1
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0answers
4 views

What is generally the best way to combine tabular image metadata with image data in a convolutional neural network?

I have 26 features from tabular data (clinical variables from patients like age gender etc) that I want to add to my cnn which is using xray images from patients. I am using the inception network. ...
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0answers
10 views

What's the best solution to find distance of an object to camera

i have a object with known size and i want to know that's distance from camera and camera angle,there is any way to do this? (i have single source(camera))
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0answers
17 views

Tensorflow-gpu cannot use Nvidia GPU with CUDA

I'm working on a Python Keras/Tensorflow image recognition script (on Ubuntu 18.04) which works ok, but it will only train on CPU (which is slow) and I want to be using my GPU (i have a Nvidia Geforce ...
1
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1answer
31 views

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 ...
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0answers
8 views

Augmentation techniques for dimesionality reduction of feature vector

Given a pre-trained CNN model, I extract feature vector of images in reference and query dataset with several thousands of elements. I would like to apply some augmentation techniques to reduce the ...
1
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0answers
15 views

What does “episodic training” mean?

I'm reading the book Hands-On Meta Learning with Python, and in Prototypical networks said: So, we use episodic training—for each episode, we randomly sample a few data points from each class in ...
1
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1answer
27 views

How to track performance of your model during experimenting?

During weeks and months of your work, many things may change, for example : You may modify the loss function Your training or validation datasets may change You modify data augmentation Which tools ...
1
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0answers
19 views

Where can I upload a large photo database for public access?

I am applying for a grant, and one of the tasks we are seeking funding for is to make a large image database publicly available for users to train artificial intelligence (convolutional neural network)...
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0answers
11 views

Web request stream prediction neural network architecture

Predicting near future requests in request stream is vital to improving intermediate performance memory (cache, or buffer). In this project we are gonna use neural networks you are required to to ...
2
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0answers
17 views

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 suggest an ...
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0answers
14 views

State of the art in voice recognition

In the media there's lot of talk about face recognition, mainly with respect to identifying faces (= assigning to persons). Less attention is paid to the recognition of facially expressed emotions but ...
1
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1answer
23 views

Q-learning problem wrong policy

I am coding out a simple 4x4 grid game whereby the agent starts at a particular state and his aim is to reach the terminal state. The agent is supposed to avoid traps along the way and reach the end ...
1
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0answers
10 views

How do I build a multi RNN network with keras?

I have 2 (independently long) sequences (a and b) of feature vectors that I want to use as input for a neural network. The idea was to build 2 GRU based encoders (one for each sequence). I would than ...
1
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0answers
16 views

What is the expected value of an IOU in this case?

I have a detection problem. An object with a probability of 0.5 is in a box with coordinates ((0,0), (2, 2)) and with a probability of 0.5 a box with coordinates ((2,0), (4,2)). What is the maximum ...
1
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0answers
21 views

OCR - Text recognition from Image

I plan to develop OCR application using tensorflow to get the value from the image. Text in the image may handwritting or text printed. From the image, my ocr appplication will able to get the value ...
2
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1answer
26 views

Do we need an explicit policy to sample $A'$ in order to compute the target in SARSA or Q-learning?

I would much appreciate if you could point me in the right direction regarding this question about targets for SARSA and Q-learning (notation: $S$ is the current state, $A$ is the current action, $R$ ...
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0answers
10 views

Do L2 regularization and input normalization depend on sigmoid activation functions?

Following the online courses with Andrew Ng, he talks about L2 regularization (a.k.a. weight decay) and input normalization. Now, the argument is that L2 regularization make the weights smaller, ...
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0answers
14 views

Finding unique faces in a video

I am trying to find unique (distinct) faces in multiple videos files. What is the best way to do that?
2
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0answers
13 views

Getting started with creating a general AI based on textual and then image based data?

I have a pool of knowledge that I want to mine for information and allow an AI to deduce likely conclusions from this information. My goal is to give the AI a set of textual data that is rated on a ...
2
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1answer
18 views

In deep learning, is it possible to use discontinuous activation functions?

In deep learning, is it possible to use discontinuous activation functions (e.g. one with jump discontinuity)? (My guess : for example, ReLU is non-differentiable at a single point, but it still has ...
0
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1answer
28 views

Understanding the loss function in deep Q-learning

I am trying to understand how deep Q learning (DQN) works. To my current understanding, each $Q(s, a)$ functions is estimated to be a function of a feature vector of its state $\phi$(s) and the weight ...
1
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1answer
33 views

What class of problem is this?

If I have a lot of input output pairs as training data <float Xi, float Yi> and I have a parametrized approximation function (I know the function algorithm, ...
5
votes
1answer
41 views

What is the intuition behind TD($\lambda$)?

I'd like to better understand temporal-difference learning. In particular, I'm wondering if it is prudent to think about TD($\lambda$) as a type of "truncated" Monte Carlo learning?
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0answers
8 views

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 ...
1
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1answer
38 views

What is the difference between the epsilon greedy and softmax policies?

Could someone explain to me which is the key difference between the epsilon greedy policy and the softmax policy? In particular in the contest of SARSA and Q-Learning algorithms. I understood the main ...
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0answers
10 views

off-policy evaluation in reinforcement learning

IPS estimator, which is used for off-policy evaluation in a contextual bandit problem, is well explained here: Doubly Robust Policy Evaluation andOptimization https://arxiv.org/pdf/1503.02834.pdf ...
1
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0answers
12 views

EEG and Accelerometer Neural Network

I have frequency EEG data from fall and non-fall events and I am trying to incorporate it with accelerometer data that was collected at the same time. One approach is, of course, to use two separate ...
1
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0answers
10 views

Feeding a neural network with single slices of a 3D matrix

I'm working on a neural network wich "slices" a 1080p image in many layers. It takes a 1080p image as an input and produces a 1080*1920*n matrix: basically I add a z value to each pixel rapresenting ...
2
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0answers
14 views

What are evolutionary algorithms for topology and weights evolving of ANN (TWEANN) other than NEAT?

I wonder, if there are other than NEAT approaches to evolving architectures and weights of artificial neural networks? To be more specific: I am looking for projects/frameworks/libraries that use ...
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0answers
18 views

Porting from Python to Octave [closed]

I am trying to solve a problem in deep reinforcement learning. In order to better debug issues, I rendered a simplistic version of the environment in Python in order to be able to use the Pytorch ...
2
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0answers
30 views

CNN for image-to-image mapping

I am working on a problem in which I need to train a neural network to map one or more input images to one or more output images (1 channel for image). Below I report some examples of input&output....
-1
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0answers
26 views

How could one track the feature locations in a convolution neural network?

A major problem with deep learning, according to Hinton, is that operations like max-pooling remove the position information of features with respect to each other. How one might attempt to track ...
1
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0answers
9 views

Scoring feature vector with Support Vector Machine

I am reading the R-CNN paper by Ross Girshick1 et al. (link) and I fail to understand how they do the inference. This is described in the section 2.2.Test-time Detection in the paper. I quote: At ...
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0answers
43 views

Data scientist vs autoML?

In the future, how will a data scientist outperform some platforms like autoML?
2
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0answers
17 views

Lego minifigure facial recognition: where to start?

I'm interested in starting a project that will identify the face of a Lego minifigure from a digital photo. I eventually want to do a "face swap," but I'd like to start with the challenge of ...
1
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0answers
62 views

Expected SARSA, SARSA and Q-learning

I would much appreciate if you could point me in the right direction regarding this question about targets for approximate ...
1
vote
0answers
11 views

How to build sort objects model using Deep Learning

How to build sort objects model using Deep Learning if i have some objects in an image enter image description here if i give him an similar image he sort the detected order according to Learning ...
2
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0answers
32 views

Why is this Monte Carlo approach scalable for a growing number of states variables and action variables?

I am reading a research paper on the formulation of MDP problems to ICU treatment decision making: Treatment Recommendation in Critical Care: A Scalable and Interpretable Approach in Partially ...
2
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2answers
44 views

Why does the bias need to be a vector in a neural network?

I am learning to use tensorflow.js. I am also using the tfvis library to print information about the neural net to the web browser. When I create a create a dense neural net with a layer with 5 ...
0
votes
0answers
21 views

How to use Before / After images to train a model

I am trying to create a model that can clean pictures of noise, blur, high luminosity etc, but I do not know how to do that. I have tried to search for it a lot, and I couldn't find anything that ...
1
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0answers
13 views

Searching for powerfull AI modules to improve teef gloves

I have seen the teef glove ofNavid Azodi and Thomas Pryor, like this : and also seen this post which has been said about this kind of work problem : Their six-page letter, which Padden passed ...
1
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0answers
35 views

How is clustering used in the unsupervised training of a neural network?

How is clustering used in the unsupervised training of a neural network? Can you provide an example?
1
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1answer
75 views

In which cases is the categorical cross-entropy better than the mean squared error?

In my code, I usually use the mean squared error (MSE), but the TensorFlow tutorials always use the categorical cross-entropy (CCE). Is the CCE loss function better than MSE? Or is it better only in ...
2
votes
0answers
16 views

Can Bert be used to extract embedding for large categorical features?

I've lot of training data points (i.e in millions) and I've around few features but the issue with that is all the features are categorical data with 1 million+ categories in each. So, I couldn't use ...
2
votes
0answers
23 views

How can I train a Deep Learning model using degraded photos and their clean version to correct photos

I have 5000 degraded pictures ( pixelated, blurry, too much luminosity ... ) and their clean versions, and I would like to train a model so that it can predict how to correct future pictures. I've ...
2
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0answers
20 views

How do I determine the best neural network architecture for a problem with 3 inputs and 12 outputs?

This post continues the topic in the following post: Is it possible to train a neural network with 3 inputs and 12 outputs?. I conducted several experiments in MATLAB and selected those neural ...

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