Questions tagged [machine-learning]

For questions related to machine learning (ML), which is a set of methods that can automatically detect patterns in data, and then use the uncovered patterns to predict future data, or to perform other kinds of decision making under uncertainty (such as planning how to collect more data). ML is usually divided into supervised, unsupervised and reinforcement learning. Deep learning is a subfield of ML that uses deep artificial neural networks.

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160 views

Is it possible to learn to estimate the minimum value in a table?

Is it possible to classify or learn to estimate the minimum value in a table if the values are integer and represented 32 bits (and we can input all variables at the same moment, like in system on a ...
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71 views

What are suitable predictive analytics models for data from multiple sensors?

I am a newbie in the field of AI/ML. I am trying to implement predictive analytics model on the data generated and collected every minute from a device with sensors. I have two questions: What are ...
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38 views

Is there a general adversarial network that can take multiple low quality images to create a higher quality image?

Is there a general adversarial network that can take multiple low quality images of a subject to create a higher quality image of the subject? SRGANS just take a single low res image and make it high ...
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205 views

Can anybody explain such behavior of accuracy and loss of my Net(caffe)?

I used this project for example(framework - caffe, arhitecture of net - mod of AlexNet, 400 images are used for training). I have this result: or this: Solver: ...
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73 views

Advanced NLG - robot journalist

I want to produce a bot in Python that automatically generates short football summaries from Whoscored data. For my first stage I generate the articles with different sentence templates and lots of ...
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377 views

CNN attention maps on non-images

My datasets are not actual images, so using methods with ImageDataGenerator or pre-trained networks might not apply in this case. Data Structure: Each "image" is a 2048-long vector that has float ...
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116 views

Train, Validation and Test Split for Reporting Accuracy of Neural Model and BOW

I need to report accuracies of my neural model in a conference paper as compared to various baselines. What are the accepted standards for reporting accuracies in a fair manner? Neural Model: To be ...
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70 views

seq2seq vector to letters model

I'm looking to build a sequence-to-sequence model that takes in a 2048-long vector of 1s and 0s as my input and translating it to my known output of (a variable length) 1-20 long characters (ex. ...
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1answer
135 views

How do I classify an image that contains only polygons?

I have two closed polygons, drawn as connected straight black lines on a white background. I need to classify such images in to three forms Two separate polygons One polygon encloses the other The ...
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1answer
138 views

possible to train some model to recognize trash?

I want to build a semi autonomous robot/machine that will clean up trash in cities. For this to be possible it needs to recognize 'trash'. As trash can be all sorts of things (think ciggaret buts, ...
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29 views

Generating fake faces containing specific features with GANs

I'm trying to understand how DeepFakes are generated and so far I understood that they're mostly generated through the usage of GANs and autoencoders. The autoencoders part is understandable, but what ...
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30 views

How to use unmodified input in neural network?

My question may be a bit hard to explain... My neural network learns a categorical distribution, which serves as an index. This index will look up the value (= action_mean) in Input 2. From this ...
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28 views

Which ML approach could determine that a number greater than 5 is not prime, knowing that a number is not prime if it ends with an even digit or 5?

I have started studying ML just a short while ago, so that my questions will be very elementary. That being so, if they are not welcome, just tell me and I'll stop asking them. I gave myself a ...
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38 views

Where can I find pre-trained agents able to play games with multiple stages like exploration, dialog, combat?

My goal is to create an ML model to be able to classify different game stages, e.g., dialog with a non-player character, exploration, combat with enemy, in-game menu etc. In order to do that, I am ...
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18 views

Is case-based-reasoning a machine learning technique?

A few years ago when I was in university, I had implemented (for my final year project) an Itinerary Planning System, which incorporates an AI technique called "case-based reasoning". Is ...
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40 views

How to design my Neural Network for Game AI

For my school project, I have to develop an agent to play my game. The base I have is a 'GameManager' which call 2 AIs, each taking a random move to do. To make my AI perform, I decided to make a ...
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36 views

How am I supposed to code equation 4.57 from the book “Machine Learning: An Algorithmic Perspective”?

Consider the equation 4.57 (p. 108) from section 4.6 of the Book Machine Learning: An Algorithmic Perspective, where the derivative of the softmax function is explained $$\delta_o(\kappa) = (y_\kappa -...
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21 views

Can any area of math come into play in Machine Learning Research?

As I read online following areas in mathematics comes into play in ML research Linear Algebra Calculus Differential Equations Probability Statistics Discrete Mathematics Optimization Analytic ...
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28 views

Can XGBoost solve XOR problem?

I've read that decision trees are able to solve XOR operation so I conclude that XGBoost algorithm can solve it as well. But my tests on the datasets (datasets that should be highly "xor-ish"...
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26 views

How do I derive the gradient of the log-likelihood of an RBM?

In a Restricted Boltzmann Machine (RBM), the likelihood function is: $$p(\mathbf{v};\mathbf{\theta}) = \frac{1}{Z} \sum_{\mathbf{h}} e^{-E(\mathbf{v},\mathbf{h};\mathbf{\theta})}$$ Where $E$ is the ...
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21 views

Would performance of atomic models matter in ensemble methods?

Suppose I have two fitted ensemble models $F_1 := (f_1, f_2, f_3, \cdots f_n)$ and $G_1 := (g_1, g_2, g_3, \cdots g_n)$. And they were using the same ensemble methods (boosting or bagging). And I am ...
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20 views

Machine Learning Techniques for Objects Location/Orientation in Images

what Machine Learning tool can understand in which location and orientation a picture was taken from? That is from pictures of similar objects, say for example pictures of car interiors. So given a ...
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18 views

Neural network algorithm implementation for Iris dataset

I want to use Neural network algorithm over famous Iris dataset. Iris dataset attributes names sepal length in cm sepal width in cm petal length in cm petal width in cm Sample dataset: ...
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9 views

How do you make a regression model from a binary labeled dataset?

Suppose I have a dataset with hand images. Hand completely opened is labeled as 0 and hand completely closed (fist) are labeled as 1. I also have a bunch of unlabeled images of hands which, if ...
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11 views

Multiple Inertia sensors system based for gestures recognition

I am a newbie to Machine Learning field as I am engaging to a personal project that I am trying to use the 6 degree of freedom Inertial Measurement Units(IMUs) measuring the Acceleration acting on 3 ...
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18 views

Literature on computational modelling involving neuronal ensemblies

Straying from the current trends in deep learning, there is an, arguably, interesting idea of neuronal ensembles possibly providing an alternative to the current "layered feature detectors" ...
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53 views

How differentiable programming and programming language supporting it will potentially help the development towards AGI?

After the state of the art Deep Learning techniques/algorithms being implemented in low-level languages like Objective-C, C++, etc to high-level languages like Python, JS, etc. and with the help of ...
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46 views

How much should we augment our training data?

I am wondering how much I should extend my training set with data augmentation. Is there somewhere a pre-defined number I can go with? Suppose I have 10000 images, can I go as far as 10x or 20x times, ...
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Neural Network for locating shifting resonant frequencies

I have multiple FFT's taken from a sample at different pressures, through different analysis I can see that the resonant frequencies are shifting in the spectrum for each FFT at a different pressure. ...
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33 views

Any AI software to help finding funding for AI projects?

Do you know of some paper mentioning a running AI system (preferably open source) that helps finding funding for AI software development? Obviously, be funded for working on AI is not easy, and could ...
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14 views

Why is domain adaptation and generative modelling for knowledge graphs still not applied widely in enterprise data? What are the challenges?

I see that domain adaptation and transfer learning has been widely adopted in image classification and semantic segmentation analysis. But it's still lacking in providing solutions to enterprise data, ...
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1answer
58 views

How is exponential moving average computed in deep Q networks?

In normal Q-learning, the update rule is an implementation of the exponential moving average, which then converges to the optimal true Q values. However, looking at DQN, how exactly is the exponential ...
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32 views

What Classification Algorithm Do I need to Use to Solve this Problem?

I am trying to solve the following problem it is to classify the the red points and green points in image 1 into two cases. The cluster of green or red points can be anywhere and there can be any ...
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14 views

Human intuition behind SVD in case of recommendation system

This does not answer my question. I struggled very hard to understand the SVD from a linear-algebra point of view. But in some cases I failed to connect the dots. So, I started to see all the ...
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26 views

What's the difference between domain randomization and domain adaptation?

In my understanding, domain randomization is one method of diversifying the dataset to achieve a better shot at domain adaptation. Am I wrong?
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24 views

Can I use ML to discover via videos the best place to shoot in foosball?

I am a programmer, but just now attempting to enter the world of ML. I'm eyeballing a potential project/problem related to foosball. Pro foosball is a thing believe it or not and I'm wondering if I ...
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1answer
68 views

Is gradient descent scale invariant or not?

I know we should scale the input and output (assuming regression task) before we feed it to the neural network. Then the gradient descent will give the better minima much faster. But I have subtle ...
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55 views

What is the best way to make a deep reinforcement learning environment with a continuous 2D action space?

I understand that the actor-critic method is probably where I want to start because of how it works with continuous action spaces. However, the problem I am trying to solve would require the action be ...
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44 views

Plotting loss vs number of updates made and plotting loss vs run time

I wanted to plot a graph to show the effect of increasing the batch size on loss calculated (MNIST dataset). But I am not able to decide if I should show change in loss over training time of the ...
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77 views

Ways to keep up with the latest developments in Machine Learning and AI?

With over 100 papers published in the area of artificial intelligence, machine learning and their subfields every day (source), accounting for ~3% of all publications world wide per year (source) and ...
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40 views

Can I apply AdaBoost on a random forest?

I know the random forest is a bagging technique. But what if my random forest overfits on a dataset, so I reduce the depth of the decision tree and now it is underfitting. In this scenario, can I take ...
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1answer
70 views

How to solve the “dangerous feedback loops” in machine learning?

From the article Dangerous Feedback Loops in ML Let’s say our model has leads from Facebook, Google, and Bing. If our first model decides that the probability of conversion is 3%, 5%, and 1% from ...
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33 views

Could a quantum computer perform vectorized forward propagation in deep networks?

Forward propagation in Deep Neural Networks In the "Forward Propagation in a Deep Network" video on Coursera, Andrew NG mentions that there's no way to avoid a for loop to loop through the ...
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66 views

Why are these same neural network architecture giving different results?

I tried the first neural network architecture and the second one, but keeping all other variables constants, I am getting better results with the second architecture. Why are these same neural network ...
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40 views

Can text-independent writer identification be done without multi-sentence training datasets for each writer?

I am trying to learn more about text-independent writer identification and was hoping for some advice. I have a folder with 100k images, each of them with a different handwritten sentence. All of the ...
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1answer
80 views

Binary mode or Multi-label mode is correct when using binary crossentropy and sigmoid output function on multi-label classification

I would like to ask a question about the relationship of accuracy with the loss function. My experiment is a multiclass text classification problem, and I have built a Keras neural network to tackle ...
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1answer
57 views

Is it possible that every class has a higher recall than precision for multi-class classification?

I am a student learning machine learning recently, and one thing is keep confusing me, I tried multiple sources and failed to find the related answer. As following table shows (this is from some paper)...
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2answers
81 views

Why the cost/loss starts to increase for some iterations during the training phase?

I am trying to build a recurrent neural network from scratch. It's a very simple model. I am trying to train it to predict two words (dogs and gods). While training, the value of cost function starts ...
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30 views

Tic-tac-toe: How would standard SARSA and Q-learning yield different results in the agent's behaviour?

I know this is deceptively simple. Tic tac toe is a well studied game for RL. Assume your agent is playing aggainst a strong opponent. I know you deal in after states. I know that in Q learning the ...
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29 views

How to measure/estimate the energy consumption of CNN models during testing?

Does someone know a method to estimate / measure the total energy consumption during the test phase of the well-known CNN models? So with a tool or a power meter... MIT has already a tool to estimate ...

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