Questions tagged [machine-learning]

Questions about computer algorithms that automatically discover patterns in data and make good decisions based on them.

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7 views

How to get developers to contribute my open source project (SIMD intructions, Numerics)?

I have a project in my mind that I have been developing on github. It's a heavily optimized numeric library that helps you to do numerical operations without lack of performance. I contest with Intel ...
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The No-Free-Lunch Theorem and K-NN consistency

In computational learning, The NFL theorem states that there is no universal learner. For every learning algorithm , there is a distribution that causes the learner to output a hypotesis with a large ...
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what is the right strategy for labelling images to recognize table and understand data

I am trying to build a model to detect tables from images of machine plates(PFA) and create key/value pairs of the information present in the table. But I am not very sure that what is the best way to ...
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What is the purpose of standardization in machine learning?

I'm just getting started with learning about K-nearest neighbor and am having a hard time understanding why standardization is required. Reading through, I came across a section saying When ...
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37 views

Are chatbots a good example of overfitting?

In my highschool class we are learning about Artificial Intelligence, and especially the problems that come with machine learning. I was wondering if chatbots like cleverbot were good examples of ...
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How to transform an arbitrary graph into a fixed vector representation?

Actuality I work in computer vision, specifically on a problem known as "scene graph modeling." This problem aims to convert an image $I$ in a graph $G=(V,E)$ where the nodes $V$ represent the objects ...
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15 views

How to initialize the first h in an RNN?

Take a Vanilla RNN represented by the function $h_t = f(h_{t-1}, x_t)$, how do you determine $h_0$? Edit: This answer over on the stats page has helped.
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Learning the weights in a directed acyclic graph

I have a directed acyclic graph $G=(V,E)$ where each vertex $v$ is associated with a weight $w_v$ such that $$w_v=1+\sum\limits_{(v,v')\in E} w_{v'}$$ and $w_v=1$ in case $v$ is a leaf. I am trying ...
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What is the difference between derivative free optimization and derivative optimization in terms of advantages/disadvantages?

I understand the basic operation of the algorithms however i'm unclear as to when to use one over the other and what advantages/disadvantages they offer over each other. Also as an aside, if anyone ...
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15 views

(machine learning) How to create a model which predicts the radius of a circle?

My training set is made up of 2d images with one imperfect but broadly circular shape in them (plus plenty of noise). I wish to train a model to predict the "radius" (obviously it's a somewhat ...
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Clustering - Complete Linkage draw example

I'm studying unsupervised learning methods (clustering) and i've seen the Complete Linkage Method. I've also seen the following statement: Unlike single linkage, the complete linkage method can be ...
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27 views

Recover boolean vector from dot products

Question: I want to determine a boolean vector $b \in \{0,1\}^n$ consisting of zeros and ones, but cannot access it directly. I can only call a black-box computer code which will take the dot product ...
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Does the weighted max cut problem have applications to machine learning? If so, what are they?

At first, I thought the weighted max cut problem (WMCP) could be of use to binary classifiers, but since the standard WMCP doesn't have any "node groups must be on opposite side of a straight line" ...
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CNN Predicting One Class and Accuracy Getting Stuck

My model is a binary classifier. With the same exact architecture, the model sometimes gets high accuracy (90% etc), other times it predicts only one class (so accuracy is stuck at one number the ...
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Model suggestion for detection of malware based on multiple api call sequences

I'm trying to build a RNN (LSTM) model for classification of binary as benign/malware. The data structure I've presently looks as follows ...
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What is the official name of a specific type of combination algorithm

Say that I have the following set of variables: [A,B,C,D,E,F,G,H,I,J,K,L,M,N,O,P,Q,R,S,T,U,V,W,X,Y,Z] The values represent a list of variables from a dataset. ...
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Can Hidden Markov Models be used for real-time analysis?

From what I understand, HMMs construct a underlying sequence of states to maximize the probability of a sequence of observations. As far as I can tell, that should make them inappropriate to use ...
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Value flow (and economics) in stacked reinforcement learning systems: agent as reinforcement environment for other agents?

There is evolving notion of stacked reinforcement learning systems, e.g. https://www.ijcai.org/proceedings/2018/0103.pdf - where one RL systems executes actions of the second RL system and it itself ...
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How would you generate files with several different rules?

Okay, the title is kind of cryptic because I'm lacking terminology (part of the problem). Situation Let's say you want to generate data corresponding to one specific, standardized paper document. ...
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Query about an equation in GAN-NMT paper

So i was studing the paper Adversarial Neural Machine Translation by Lijun Wu1, Yingce Xia2, Li Zhao3, Fei Tian3, Tao Qin3, Jianhuang Lai1,4 and Tie-Yan Liu. The link to the paper is : https://arxiv....
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How is knowledge of lambda calculus applicable in Computer Science and Machine Learning? [closed]

If I want to do research in computer science and machine learning, is it important to have a well-rounded understanding of lambda calculus?
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True Error of a binary classifier

For a given classifier h, How is the true error over a distribution D defined? \begin{align*} L_D(h) &= \sideset{\mathbb{E}}{}{}_{x,y \sim D} \Pr[h(x) \neq y] \\ &= \sideset{\mathbb{E}}{}{}_{x,...
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Optimising matketing budget on marketing and sales data

I have a dataset from business where the variables include investment across diferent channels and independent variable is the sales. I have developed a marketing mix model using linear regression to ...
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Understanding Multi-headed attention

Recently I came across the concepts like Attention and Transformer architecture. After studying the papers and many blogs, I understood the concepts, but recently one doubt is coming in my mind and ...
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27 views

Which computational framework lies behind the Chinese “Social Credit System”?

BACKGROUND The Social Credit System is a data-driven reputation system which draws on several sources to label various entities, namely businesses and individual citizens, with a trustworthiness ...
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How do I input (magnitude of) numerical data in CNN/U-net like architectures?

I've been given some (latitudes,longitudes) points with cellular signal strength(float numbers) on those particular points. And I've been given the location, (lat,longs) of cellular towers in a ...
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Agnostic PAC learnable hypothesis class for binary classification

I'm trying to prove that any agnostic PAC learnable class $\mathcal{H}$ of binary classifiers is PAC learnable (with respect to the 0-1 loss function), which means that for any density distribution $\...
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Is it useful to transform a regression problem into a classification one?

First, I would like to say that I understand the difference between a classification problem and a regression one. Let's imagine that I'm trying to predict the time of a sprinter to run 100 meters ...
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Learning Specific Topics In Machine Learning [closed]

I am a beginner in machine learning and I already have a good linear algebra/calculus background. I am interested in being able to eventually understand and implement convolutional neural networks, ...
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53 views

Search vs planning in artificial intelligence

I'm studying artificial intelligence following the Russell & Norvig book. We did a search and planning part that for me is the same (at least on the representation). I'd like to know what is the ...
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How does the Random Forest classification function

I was going the through Random forest classification trying to understand it and I stumbled on two equation and I was wondering if anyone knows their name. what are the names of the theorms or ...
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32 views

Introduction to computer science for ML [closed]

I have learned python syntax (from books like fluent python or python cookbook etc.) and I want to learn the underlying concepts of computer science (in an abtract way), do you have some books/courses ...
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20 views

Dimension Reduction - Which feature should remove to reduce the dimension of the matrix

Let's suppose that we have the following 2 tables: If we want to reduce the dimension by one(in every table) which feature we should remove and why ? I am confused about the way that i should work ...
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Is it possible to compute a whole convolution layer at once?

I have an input of 32×32×3 and I want to feed it to a convolution layer that output 32×32×16 feature maps. I know that I can compute a single feature map as matrix multiplication. But my question is, ...
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Cross Entropy Function

I've seen two versions of the cross entropy cost function, and conflicting information about it. \begin{equation}J(\theta) = -\frac{1}{N} \sum_{n=1}^N\sum_{i=1}^C y_{ni}\log \hat{y}_{n_i} (\theta)\end{...
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Simple Question About the Nature of Supervised Learning Predictive Models in Relation to their Training Data

Would a deployed or deployment-ready (i.e., already-trained) supervised learning model have a 100% accuracy rate for predictions on the training data (if you were to run the training data through it ...
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Is there any intersection in the applications of multi-agent reinforcement learning and more traditional branches of machine learning?

From my limited understanding, it seems like the structure of problems that multi agent reinforcement learning attempts to attack is quite different from the structure of problems in more traditional ...
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Linear regression: not noramalising by y's norm

I was recently reading an article on Pearson correlation, and OLS coefficients. I came across the following section. Finally, these are all related to the coefficient in a one-variable linear ...
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42 views

What is the best algorithm known to learn the regular expression from a set of positive examples?

I have a blackbox program that generates a set of strings. What is the best regular expression learner that I can use to learn (approximate) what the blackbox program uses as a generator? Note that I ...
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maximum tensor rank for computer vision tasks

Most computer vision tasks do not require 4+ ranked tensors. Are there any use cases for tensors with ranks more than 4 in computer vision? Are there any use cases for deep learning in general?
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Prior probability in HMM

This is the HMM model considered in the question And this is the emission probabilities for the respective states. There are two emission values, bringing an umbrella and not bringing an umbrella. ...
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how can i find that the size of tree which is built by C5.0 algorithm is good?

I built C5.0 for balancing data with 16 attributes. and the size of my model is 125 and it used 15 attributes for building model.how can i find the size is good?
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Question about implementing GAN(Generative Adversial network)?

so most examples I've seen create two NN-s, train them, then they stack them, make the discriminator part untrainable and then train this stacked NN, why do we do this? So loss, that is calculated on ...
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Data points as outcomes of a random experiment

It is well known that Random variable is a function from sample space of a random experiment to $\mathbb{R}$. Consider the following sentences from deep learning book Let $\{x^{(1)}, \cdots , x^{...
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Why is Agnostic PAC learnability a stronger criterion as compared to the PAC learnability?

I am trying to understand the mentioned question. According to me, it should be other way around as it is easier to find hypothesis which is approximately correct compared to the optimal hypothesis in ...
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40 views

What is the most efficient way to test whether a set $X \subset \{0, 1\}^n$ and its complement $\{0, 1\}^n \setminus X$ are linearly separable?

I am interested in algorithms that have optimal running time, and ideally which are also very easy to implement. If you can also give some tips on how to implement the algorithm(s) you mention in the ...
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Which time series prediction techniques are useful given harmonic properties?

I have a time series dataset where events have harmonic properties, and seemingly the nature of the event's early segments can determine the remainder of the event (see example 1's oscillations). ...
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28 views

Weighting function for Non Uniform Learning

Consider a hypothesis class $H = \cup_{n=1}^{\infty} H_n$, where for every $n\in N$, $H_n$ is finite. Find a weighting function $w : H ->[0, 1]$ such that $\sum_{h \in H} w(h) ≤ 1$ and so that for ...
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How to compute the derivative using chain rule of hidden layer (more than 5 neurons for hidden layer) with bias

In the given problem having 8 inputs with 5 hidden layers and 3 output layers and bias(b1) on hidden layers and bias(b2) on ...
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Sorting using AI / neural net

I have a search operation taking place on a server that essentially queries images using OpenCV against other images from a database. Since each image query ...