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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20 views

Binary classification for a series of data (using Keras) to tell if it is a straight line or not a straight line

I am new to machine learning and I would like to seek some advice/help for directions on implementing a binary classification for a series of data and tell if it is a straight line or a not? for ...
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27 views

Sails size recognition

Is it possible to recognize the height and width of the sails of different kitesurfers and windsurfers taken from public webcams? And show these information on video in real time? Or on screenshots?
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36 views

How to deal with Neural network input data with different length and type

I'm trying to make use of sensor data from VOC, Humidity, Age, Sampling rate and use them as NN input data. Below are the technical questions I'm struggling to find out. For each training set, I have ...
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35 views

Estimate distance between points in perspective image

I am trying to estimate the real world distance (in metres) between two points in a perspective image using an uncalibrated camera. However, the dimensions of an object in the image are known. I ...
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95 views

What is the right formula for weight update rule in Logistic Regression using stochastic gradient descent

Apologies for the lengthy title. My question is about the weight update rule for logistic regression using stochastic gradient descent. I have just started experimenting on Logistic Regression. I ...
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39 views

Should I use the hyperbolic distance loss in the case of Poincarè Disk Model?

I trained a neural network which makes a regression to a Poincarè Disk Model with radius $r = 1$. I want to optimize using the hyperbolic distance $$ \operatorname{arcosh} \left( 1 + \frac{2|pq|^2|...
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Is action model learning with machine learning techniques feasible?

In the control theory, a forward model describes predicted behaviors of a system. A forward model of a car physics can calculate the position of the car with x/y value if the steering wheel is put in ...
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125 views

What are the key differences between cellular neural network and convolutional neural network?

What are the key differences between cellular neural networks and convolutional neural networks in terms of working principle, implementation, potential performance, and applicability?
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How to predict a preferred route based on weather and distance

I want to train a neural network to predict what my favourite home-work route will be for a particular day. I have these features for routes on a day: ...
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42 views

Algorithms to indentify people in pictures without using face recognition

There are lot of researches about face detection in pictures, but is it the only way one can say "this person I'm looking for is here in this picture"? Aren't there algorithms that you can provide ...
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81 views

How to build a neural network that can learn to predict output images?

I am working with a dataset where each input sample is a matrix, and the output corresponding to each input is also a matrix (of shape (400, 10)). The input samples ...
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What methods are there to generate artificial training examples based on existing training examples?

I have a small dataset (117 training examples) and many features (4005). Each of the training examples is binary labeled (healthy / diseased). Each feature represents the connectivity between two ...
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127 views

When to use which metric in machine learning?

In machine learning, there are several metrics to assess the quality of the models: accuracy, precision, recall, f measure, ROC (AUC), etc. There are cases when certain metrics are more appropriate ...
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77 views

Reinforcement learning for inventory management with dynamic changes to available products

Consider a shop owner who has to deal with having to buy for one week from a different supplier with several different brands. Another week a brand is removed or added from the market. Yet another ...
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83 views

How to perform unsupervised anomaly detection from log file with mostly textual data?

I have a log file of the format, Index, Date, Timestamp, Module, App, Context, Session, Verbosity level, Description The log file can be considered as a master log, which consists of individual ...
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132 views

How do the sine and cosine functions encode position in the transformer?

After going through both the "Illustrated Transformer" and "Annotated Transformer" blog posts, I still don't understand how the sinusoidal encodings are representing the position of elements in the ...
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1answer
50 views

What would be the steps to create an sentiment analysis chatbot?

We have been assigned a project, in which we have to create a chatbot which will ask question, take the replies, analyse them and give an approximate assessment of the current emotional state of the ...
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1answer
153 views

Anomaly Detection in distributed system using generated log file

I am developing an AI tool for anomaly detection in a distributed system.  The system supports an interface that combines several individual logs into a single log file generating approx. 7000 entries/...
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49 views

How can my Neural Network categorize message strings?

Abstract I wish to design a neural network that will categorize messages based on criteria I have predefined. It should feature the ability to be proactively trained as it continues its lifecycle. ...
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76 views

How do PGMs factor in to modern ML?

I just finished the three-part series of Probabilistic Graphical Models courses from Stanford over on Coursera. I got in to them because I realized there is a certain class of problem for which the ...
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2answers
99 views

Which neuron represents which part of the input?

In a neural network, each neuron represents some part of the input. For example, in the case of a MNIST digit, consider the stem of the number 9. Each neuron in the NN represents some part of this ...
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3answers
124 views

Extracting algebraic constraints from the input data

I would appreciate your help with this (naive) question of mine. Given the set of points located on a circle, $x_{i}, y_{i}$ as the input data, Can a deep/machine learning algorithm infer that radius ...
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305 views

What are some of the drawbacks of one-shot learning?

One-shot learning seems to work really well in many application domains. Are there any major (or even minor) drawbacks of using one-shot learning? Does it have flaws that could prevent it from being ...
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264 views

Implementing AI/ML for the card game “Cheat”

Background info In Python, I've implemented a rudimentary engine to play "Cheat", supporting both bots and a human or only bots. When only bots are playing, the game is simulated. When placing cards,...
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53 views

What kind of distributions can be used to model discrete latent variables?

If we take the vanilla variational auto-encoder (VAE), we $p(z)$ is a Gaussian distribution with zero mean and unit variance and we approximate $p(z|x) \approx q(z|x)$ to be a Gaussian distribution as ...
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Is Hebbian learning the progenitor of AI?

Hebb's postulate attempts to explain associative learning via the processes of sampling (using sensors), emitting responses and receiving feedback. This is a form of control orientated architecture ...
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1answer
89 views

Price difference predictions curve almost vanished

With a team, we are studying how it is possible to predict the price movement with high-frequency. Instead of predicting the price directly, we have decided to try predicting price difference as well ...
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39 views

Detect root cause across many event occurrences

Suppose there are sensors which supply numerical metrics. If a metric goes above or below a healthy threshold, an event (alert) is raised. Metrics depend on each other in one way or another (we can ...
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29 views

How exactly is equivariance achieved in capsule neural networks?

I have read quite a lot about capsule networks, but I cannot understand how the squashed vector would also rotate in response to rotation or translation of the image. A simple example would be helpful....
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36 views

Autoencoder why it is special for image decoding?

I have read about auto encoder. Understood what is encoding part, and decoding part, and the latent space. Now, i tried to implement this in keras. Below is the code. ...
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88 views

Mapping Actions to the Output Layer in Keras Model for a Board Game

I have created a game based on this game here. I am attempting to use Deep Q Learning to do this, and this is my first foray into Neural networks (please be gentle!!) I am trying to create a NN that ...
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44 views

What methods are there to detect discrimination in trained models?

I've been researching AI regulation and compliance (see my related question on law.stackexchange), and one of the big take-aways that I had is that the regulations that apply to a human will apply to ...
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30 views

In CNN (Convolutional Neural Network), does the combination of previous layer's filters make next layer's filters?

I know that the first layer uses a low-level filter to see the edge information. As the layer gets deeper, it will represent high-level (abstract) information. Is it because the combinations of ...
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1answer
91 views

Why do I get small probabilities when implementing a multinomial naive Bayes text classification model?

When applying multinomial Naive Bayes text classification, I get very small probabilities (around $10e^{-48}$), so there's no way for me to know which classes are valid predictions and which ones are ...
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74 views

Multiple sets of input in Neural network (or other form of ML)

I'm currently working on a research project where I try to apply different kinds of Machine Learning on some existing software I wrote a few years ago. This software will scan for people in the room ...
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79 views

How do GAN's generator actually work?

I have implemented DCGAN's myself and have been studying GAN's for over a month now. Now I am implementing the pggans but I encountered a sentence When we measure the distance between the ...
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66 views

Why do we have to solve MDP in each iteration of Maximum Entropy Inverse Reinforcement Learning?

Gradient in Maximum Entropy IRL requires to find the probability of expert trajectories given the reward function weights. This is done in the paper by calculating state visitation probabilities but I ...
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257 views

How do to mitigate or design out hidden feedback loops when designing ML systems?

Two months ago, I've found myself working on a churn detection problem which can be briefly described as follows: Assume the current date is N Use customer behavior for N-1,..N-x dates to develop ...
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0answers
517 views

Getting worse performance when training a pre-trained model with the existing class

I am training pre-trained SSD-InceptionV2-Coco to detect the "car", which is one of the classes in mscoco label. I train the model with ~50k sample from KITTI, 500k iteration with batch size 2. I ...
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365 views

Coding CGAN paper model in Keras

I was coding a CGAN model using Keras along with the paper (https://arxiv.org/pdf/1411.1784.pdf) and I wanted to try and match the models to exactly what the paper says. I knew the models presented in ...
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214 views

Deep NN architecture for predicting a matrix from two matrices

Recently my friend asked me a question: having two input matrices X and Y (each size NxD) where D >> N, and ground truth matrix Z of size DxD, what deep architecture shall I use to learn a deep model ...
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120 views

Stacked softmax layers before output

I have seen people using stacked softmax layers right at the output of neural networks designed for classification. I'm trying to understand this. Does it give any additional value? I think this could ...
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156 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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37 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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203 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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0answers
371 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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112 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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