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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24 views

Showing machine learning results to Group CEO

I am working as a Data Scientist in a non IT company(in fortune 500) and the group CEO is visiting the Data Science department after it's inception a few months back. We have models like chrun ...
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1answer
22 views

Is this learning rate schedule increasing the learning rate?

I was reading a PyTorch code then I saw this learning rate scheduler: ...
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1answer
41 views

What will change when workstations will have ARM Machine Learning Processors onboard?

lately we read that many manufacturers are forcing ARM architectures to be used on future workstations. One of ARM's recent announcements is a machine learning processor. What will change in terms of ...
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3answers
97 views

Is machine learning required for deep learning?

The answers to this Quora question say it's OK to ignore machine learning and start right away with deep learning. Is machine learning required or is useful for understanding (theoretically and ...
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1answer
20 views

Understanding the equation of the empirical error

The empirical error equation given in the book Understanding Machine Learning: From Theory to Algorithms is My intuition for this equation is: total wrong predictions divided by the total number of ...
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1answer
19 views

Prove that in such cases, it is possible to find an ERM hypothesis for $H_n$ in the unrealizable case in time $O(mnm^{O(n)})$

Let $H_1$ , $H_2$ ,... be a sequence of hypothesis classes for binary classification. Assume that there is a learning algorithm that implements the ERM rule in the realizable case such that the ...
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7 views

Looking to use AttnGAN and train it myself using my own images. Is this possible? How difficult would this be for myself to learn?

I am an artist and I am interested in training an image generating AI, specifically AttnGAN, using my own images. I would also consider hiring someone to set this up then show me how to use it, but I’...
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50 views

How to develop face recongiton program using CNN to obtain more than 95% accuracy? [on hold]

I want to develop face recognition program using convolutional neural network. Can some one tell me steps to follow to do the same? I am new to deep learning. I want to develop it on windows using ...
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7 views

How does keras `train_on_batch` return value work?

From the doc, train_on_batch() will return a scalar representing the loss and the metric. I want to know whether the loss/metric is evaluated before the weight is ...
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40 views

Are there datasets to solve differential equations in a supervised fashion?

Are there datasets to solve differential equations in a supervised fashion? More precisely, the input is a differential equation and the label should be the general solution to that differential ...
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5 views

Why word embedding such as word2vec is not used as the output layer of a seq2seq decoder?

It would make sense to make the decoder predict a smaller embedding vector instead of softmax over a large dictionary. The word having the most cosine similarity with the output embedding could be ...
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1answer
40 views

“Outside-in” versus “Inside-out” machine learning

A little background... I’ve been on-and-off learning about data science for around a year or so, however, I started thinking about artificial intelligence a few years ago. I have a cursory ...
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1answer
37 views

What is the difference between the definition of a stationary policy in reinforcement learning and contextual bandit?

A stationary policy is a function that maps a state to a probability distribution of actions. In a contextual bandit problem, a state itself does not include the history. But in a reinforcement ...
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14 views

How to recognize two different objects with the similar shape, but different size

I am using Mask-RCNN neural network. I retrained my network to detect and mask wheels of die-cast toy cars. I am using images, which present the side of the car (left or right). Sometimes the cars ...
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1answer
49 views

Markov property in maze solving problem in reinforcement learning

By definition, every state in RL has Markov property, which means that the future state depends only on the current state, not the past states. However, I saw that in some case we can define a state ...
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0answers
19 views

What are the examples of agents that is represent these characteristics?

I'm looking for examples of AI systems or agents that best represent these five characteristics (one example for each characteristics): Reactivity Proactivity Adaptability Sociability Autonomy It ...
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14 views

Intelligent reflecting surface

I wanted to know about Intelligent reflecting surface (IRS) technology. what is the application of IRS in wireless communication? what are the competitive advantages over existing technologies?
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1answer
146 views

What are the implications of the “No Free Lunch” theorem for machine learning?

The No Free Lunch (NFL) theorem states (see the paper Coevolutionary Free Lunches by David H. Wolpert and William G. Macready) any two algorithms are equivalent when their performance is averaged ...
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32 views

Question about minimizing sum of remainders

I have a set of integers [$c_1$, $c_2$, $c_3$, ... , $c_N$]. A non-negative integer D, greater than a certain threshold, divides each 𝑐𝑖 and leaves remainder 𝑟𝑖,i.e., $r_i$ can be written as $r_i=...
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58 views

Will parameter sweeping on one split of data followed by cross validation discover the right hyperparameters?

Let's call our dataset splits train/test/evaluate. We're in a situation where we require months of data so we prefer to use the evaluation dataset as infrequently as possible to avoid polluting our ...
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22 views

Vector normalization by a neural network

I'm wondering if there is a NN that can achieve the following task: Output a unit vector that is parallel to the input vector. i.e., input a vector $\mathbf{v}\in\mathbb{R}^d$, output $\mathbf{v}/\|\...
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1answer
43 views

How to deal with large (or NaN) neural network's weights?

My weights go from being between 0 and 1 at initialisation to exploding into the tens of thousands in the next iteration. In the 3rd iteration they become so large that only arrays of nan values are ...
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1answer
175 views

What are all the different kinds of neural networks used for?

I found the following neural network cheat sheet (Cheat Sheets for AI, Neural Networks, Machine Learning, Deep Learning & Big Data). What are all these different kinds of neural networks used ...
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7 views

How is Average Recall (AR) calculated for an object detection model?

After looking around the internet (including this paper, I cannot seem to find a satisfactory explanation of the Average Recall (AR) metric. On the COCO website, it describes AR as: "the maximum ...
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13 views

Predict the next best action based on previous lists of actions

I have the following problem. There is a software that I've written some time ago. Users enter customer's data in the system and there is a limited number of things (actions) that they can do/add - ...
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48 views

Is My Formula For a Neural Network correct?

I am creating a multi-layer neuron library in C# and doubtful of my understanding of neural network correctness as my answer even after the training of xor is always nearer 0.5. Here are the notation ...
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22 views

Is federated learning a privacy breach?

Is federated learning a privacy breach, given that the model transmission, for a period of time, may cause the adversarial to reach and manipulate the model and the data?
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1answer
36 views

How Machine Learning Studies Correlation?

This is my problem: I have 10 variables that I intend to evaluate two by two (in pairs). I want to know which variables have the strongest relationships with each other. And I'm only interested in ...
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0answers
34 views

What is the difference between random and sequential sampling from the reply memory?

I was working on an RL problem and I am confused at one specific point. We use replay memory so that the network learns about previous actions and how these actions lead to a success or a failure. ...
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1answer
43 views

How does the network know which objects to track in the paper “Label-Free Supervision of Neural Networks with Physics and Domain Knowledge”?

I was reading the paper Label-Free Supervision of Neural Networks with Physics and Domain Knowledge, published at AAAI 2017, which won the best paper award. I understand the math and it makes sense. ...
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1answer
28 views

Tensorflow and Keras model having same parameters, hyperparameters, weight and bias initialization give different accuracy? [closed]

I have made sure that layers,parameters, hyperparameters,kernel_initialization, bias_initialization, seed and dataset are all equal. But still the output for both the models are different. ...
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22 views

What is the best option to test the data set of images using weka? [migrated]

I have two hundred and fifty images, and extracted the features from them and put them in an Excel file, how to use the weka program so that the first 200 images for training and the remaining fifty ...
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30 views

Show that if $H$ is PAC learnable (in the standard one-oracle model), then $H$ is also learnable in the two-oracle model

Consider a variant of the PAC model in which there are two example oracles: one that generates positive examples and one that generates negative examples, both according to the underlying distribution ...
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1answer
17 views

Real time ticket similarity

I'm dealing with a "ticket similarity task". Every time new tickets arrive at the help desk (customer service), I need to compare them and find out about similar ones. In this way, once the operator ...
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1answer
39 views

Why does estimation error increase with $|H|$ and decrease with $m$ in PAC learning?

Why does estimation error increase with $|H|$ and decrease with $m$ in PAC learning? I came across this statement in the section 5.2 of the book "understanding machine learning: from theory to ...
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7 views

Learning to rank on collections of ordered objects?

Are there examples of LTR algorithms applied to variable length lists of ordered objects? E.g. perhaps 4 specific photos in a sequence layout would rate higher than another 3 or another 4 where the ...
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21 views

Threshold selection for Siamese network hyper-parameter tuning

I'm interested in modeling a Siamese network for facial verification. I've already written a simple working model that inputs feature vectors generated from two CNNs with shared weights then outputs a ...
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1answer
22 views

Image classification with an associated matrix

I have a dataset of images with 9 different classes. However, there are different categories with the same type of associated image and only can be differentiated with an associated matrix in my ...
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2answers
36 views

How to express accuracy of a regression ANN that uses MSE loss function?

I have a regression MLP network with all input values between 0 and 1, and am using MSE for the loss function. The minimum MSE over the validation sample set comes to 0.019. So how to express the '...
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2answers
41 views

Can ML be used to curve fit data based on dataset of example fits?

Say I have x,y data connected by a function with some additional parameters (a,b,c): $$ y = f(x ; a, b, c) $$ Now given a set of data points (x and y) I want to determine a,b,c. If I know the model ...
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29 views

why the sigmoid function will be 1 and 0 if we use a fully connected layer that produce a big enough positive(res negative )output

HI I am using a fully connected network that uses sigmoid if we feed a a big enough weights the sigmoid function will finally become 1 or 0 , is there any solution to avoid this ? and will this lead ...
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16 views

Which AI algorithm is great for mapping between two XML files

My work colleague got a project with a lot of work that is not hard or complicated. The problem is simple but it is a lot of work. We have two XML files with a lot of variables in it. Not only is ...
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1answer
31 views

Reinforcement learning with hints or reference model

In Reinforcement Learning, when I train a model, it comes up with its own set of solutions. For example, if I am training a robot to walk, it will come up with its own walking gait, such as this Deep ...
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1answer
38 views

How many hidden layers are needed for this training data set

I'm trying to separate classes in 3D space, the data are as in the sketch below: There are 3 classes: 0,1,2; and with the look into the sketch, it seems that I need 3 planes to separate the classes, ...
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10 views

Is there any reason to believe a ml pipeline that works on dataset A will work on dataset B where both have similar meta features?

I’m working on generating an automl pipeline(a combination of data cleaning and transformation algorithms applied to a dataset then generate a model) that works on a new dataset by looking for past ...
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1answer
23 views

Is it compulsary to normalize the dataset if doing so can negatively impact a Binary Logistic regression performance?

I am using raw data set with 4 feature variables (Total Cholesterol, Systolic Blood Pressure, Diastolic Blood Pressure, and Cigraeette count) to do a Binominal Classification (find stroke likelihood) ...
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20 views

How to build naive bayes graph from data

For an university assignment I have to use the HuginLite software to do some probabilistic inferences with different algorithms. One of these algorithms is Naive Bayes but its graph is not built ...
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15 views

Applying ML algorithms to data-sets with similar meta-features?

Is there any grounds for assuming an algorithms applied to a data-set that created a decently accurate model will perform as well on a different data-set with meta-features chosen and evaluated by ...
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1answer
43 views

Should the biases be zero or randomly initialised?

I'm initialising DNN of shape [2 inputs, 2 hiddens, 1 output] with these weights and biases: ...
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2answers
186 views

Should I use the Threadripper 2920X or Ryzen 7 3700X?

Update 2 The OS I'm using is Windows 10, since we have WSL, I also use Ubuntu to run the code. The code is written in Python. I know there are thousands of factors which affect the final performance ...