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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23 views

SMO, Random forest and Bayes net algorithms: why does Random forest perform better?

I analyzed a dataset using those 3 different algorithms. As I can see, Random forest performs better in most cases. My dataset is composed of 4000 instances of two classes (class A 2000 elements, ...
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24 views

Papers on depth separations in neural networks

I am new to the domain of Machine learning. I have been asked to present a paper related to the mathematics behind the depth separations in Neural Networks (by Itay Safran, Ronen Eldan and Ohad Shamir)...
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Conv Net dimensions misunderstanding?

I was asked this question: Given an image with shape [1,28,28], what will be the shape of the output of a convolution layer with 10 5x5 kernels (filters) without padding? Now, are the shape dimensions ...
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“Reshaping” vs Polymorphism In Data Wrangling

A lot of the work in data science -- machine learning in particular --involves "reshaping" arrays, tables, and other data structures. These data transformations are not really lossy ...
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How does Pointnet's Shared MLP work? [closed]

When reading about Pointnet's Shared MLP, I kept hearing it described as 1x1 convolution, where each point is process separately. During the Shared MLP, I understand that each point's are expanded ...
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Is MDP Considered as The Model-based Value Iteration in/of Reinforcement Learning?

Is MDP Considered as The Model-based Value Iteration in/of Reinforcement Learning? If no, then Reinforcement Learning is all about being Model-free learning. Right?
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Why did Apple include dedicated a neural network “processor” in standard consumer products?

Not sure if this is the right place, but I guess it is better than Reddit and I couldn't find any discussion. I was wondering why Apple include a neural network "processor" and can't help ...
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Monte Carlo tree search optimizations

I am designing a algoritm for a game using a Monte Carlo tree search AI that I implemented. I play against another player and want to get the best move. Every time I do a move I completely build a new ...
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1answer
36 views

What is a task type?

I have an unlabeled dataset: 500 X-rays of seeds in husk. In each image there are different number of seeds, for instance, from $10$ to $50$. A seed has some features. The main features are a seeds' ...
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29 views

Argmax in $k$-NN algorithm

Given a query instance $x_q$ to be classified Let $x_1,\ldots,x_k$ be $k$ instances which are nearest to $x_q$ $$ \hat{f}(x_q) \gets \operatorname*{argmax}_{v \in V} \sum_{i=1}^k \delta(v,f(x_i)), $$ ...
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Can the perceptron classifier achieve perfect accuracy, on any data set?

I was thinking. Since any data can become linearly seprabale through kernel methods, meaning there is a dimension where this data is linearly seprable, so feed this processed data set into the ...
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Perceptron and non linearly seprable data

I was asked in an interview question, can a perceptron classifier ever reach 100% accuracy on some kind of non linearly seprabale training data in 2D. I said that no it can't because the data is not ...
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Perceptron - Generalization Bounds & Compression Bounds

A distribution $P$ over $\mathbb{R}^{d} \times\{-1,+1\}$ being $(\gamma, R)$ -separable. We now let $\mathcal{P}_{\gamma}$ denote the set of all $(\gamma, 1)$ separable distributions. For a ...
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Machine learning algorithms for recognising national anthem song of all countries

https://en.wikipedia.org/wiki/National_anthem Are there machine learning algorithms which will recognise and interpret the national anthem song of all countries? Input dataset : National anthem sound ...
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How to predict the number of patients from the number of diagnoses

I have data on the diagnostic measures that individual patients received that year. For that individual data, I would like to make a prediction of how many such patients are in the country. To do so, ...
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Is machine learning and AI all about pattern recognition?

I realized that machine learning and AI is mostly about spamming the auto correlation and cross correlations from mathematics and combining them with memory arrays. Is it right? What do you think ...
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If we add a constant weight vector with an absolute function, does it still remain convex then? [closed]

We know that absolute functions are convex. Now what if we add a constant weight vector to it, does it still remain convex? Say the equation is Absolute loss regression + L1 regularization, we know ...
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14 views

Machine Learning - learning path

So I'm interested in learning Machine Learning and in specific in the Healthcare domain. But I'm so overwhelmed at the different learning paths the internet holds. Can someone help me out with how I ...
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1answer
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How to get a heatmap of pixel influences from a Convolutional Neural Network

If I have a CNN model (let's say I'm using Tensorflow and Keras) that I've trained for a particular task. For example, let's say I've trained it to detect the difference between an apple and banana. ...
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25 views

Is deepfake detection viable?

I'm thinking of doing a project on deepfake detection, but I'm not entirely sure if it is viable. Based on my understanding, how it works is that deepfake generation programs have a generative and ...
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1answer
16 views

which neural network is good for predecting the value of strings

I have a dataset that contains some strings. A numeric value is assigned to each string. I want to develop a machine learning (deep learning) model to get a string and predict its value. What neural ...
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16 views

How can machine learning be used in making sure a document has all the required headings and details?

We are trying to build a system that would accept fyp proposal documents and then would validate is there something missing, like a heading or a chart that should be in the document according to the ...
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Perpendicular Training Vectors SVM

Claim: If we are training a hard-margin SVM on a set of perpendicular training vectors which can either be classified as "positive" or "negative," will every training vector end up ...
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How is the RKHS norm related to sample complexity or other learning theory properties?

This is a somewhat soft question. Given two reproducing kernel Hilbert spaces (RKHSs) $H_1$ and $H_2$, if their RKHS norms only differ by a constant, i.e., $C_1\|f\|_{H_1}\le \|f\|_{H_2} \le C_2\|f\|_{...
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42 views

Density of uniform distribution over two disjoint squares

A probability distribution $P$ over $X \times \{0, 1\}$. $P$ can be defined in term of its marginal distribution over $X$ , which we will denote by $P_X$ and the conditional labeling distribution, ...
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59 views

Are most machine learning problems the same problem? (NP-hard)

I am trying to teach P vs NP to some primarily Machine Learning folks. I wanted to come up with an introductory fact to grab their attention. Reasoning for Question: Most problems in Machine Learning ...
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37 views

What is a Black Box attack against Machine Learning algorithms?

And is there an attack strategy that you can use to approximate the architecture of a machine learning system with the knowledge of class labels and some data points?
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ML Algorithm for getting top pick in each sample

I have a dataset of streets - and each street contains several houses. ...
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22 views

What is a good reference for NP hardness in the machine learning/optimization/operations research context?

I am reading some papers in machine learning and at the very beginning (introduction) you will see statements of theorems that says, for example: Theorem 1.1. For any constant ϵ > 0, it is NP-hard ...
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30 views

Expressivity of neural networks, how much information can be stored

I want to know whether a given neural network (with a finite number of nodes) is able to store all injective maps f: D -> C, where D has cardinality k and C has cardinality N (so the number of maps ...
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62 views

Empirical Risk and True Risk - Generalization Error Proof

I showed that, over an uncountable domain,learner A and a distribution P, such that for every sample size m and all samples S from $P^m$ $$ : L_S(A(S)) − L_P (A(S))| = 1 $$ Now I wanna prove for ...
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Modifying the code for reading .ogg datasets and apply LSTM

Deep learning/LSTM/Matlab There is a Matlab code that is doing the following steps for deep learning and applying LSTM, I need to change first three steps to use our dataset to train this model and ...
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36 views

Machine Learning method maps from $\mathbb{R}$ to $\mathbb{R}^2$

I have worked with image classification and image segmentation etc. While working with images we are either mapping from $\mathbb{R}^2\to\mathbb{R}$ or $\mathbb{R}^2\to\mathbb{R}^2$. Are there any ...
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What does the decision boundary of XOR problem look like?

My textbook walks through an example of solving the XOR problem in machine learning using a two-dimensional RBF network. It does this by setting the centers for the two basis functions at [0,0] and [1,...
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How to cluster a dataset in which each data point is composed of a set of 2-dimensional coordinates

I have a dataset with totally $1000$ scenarios, each of which is composed of $5$ users' coordinates $(x_i,y_i), \forall i \in \{1,\dots,5\}$. Now, based on users' coordinates, I want to cluster these $...
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1answer
17 views

SGD statistical guarantee

I have a question regard online learning with SGD. Is there a way to give a statistical guarantee that the value obtained after $n$ samples deviates at most $\epsilon$ from the real value? Thank you ...
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Comparing Directed Unweighted Graphs with Different “Densities” [closed]

I'm looking to compare 2 unweighted directed graphs and get an (ideally differentiable) similarity score. Both graphs describe a trajectory in a 2d space. The reference graph is a step by step guide ...
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1answer
35 views

Bible Verse division

I'm working on a project compiling various versions of the Bible into a dataset. For the most part versions separate verses discreetly. In some versions, however, verses are combined. Instead of verse ...
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1answer
11 views

Signal translation with Seq2Seq model

I'm currently doing some research on signal processing and I got a dataset which includes the signal in itself and its "translation". So I want to use a Many-to-Many RNN to translate the ...
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20 views

Support Vectors SVM

I have read somewhere that the value of slack variables of support vectors is not 0. Does that mean the points lying in the wrong region e.g a positive point lying in the negative region will also be ...
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With respect to differential privacy what should be the qlobal sensitivity for regression in non interactive mode?

I need to make a dataset differentially private on which regression, which in more general sense could be extended to learning any model, is to be performed. I need to calculate the global sensitivity ...
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Variant of ridge regression loss function

We can create variants of the loss function, especially of ridge regression by adding more regularizer terms. One of the variants I saw in a book is given below $min_{w \in \mathbf{R}^d} \ \ \alpha....
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Machine Learning to draw a topology of elements

I'm exploring the idea of using machine learning to draw a topology of elements. For example, imagine a tree representing geological hierarchy (country -> province -> city). All countries are at ...
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1answer
33 views

object image segmentation

I have 2 different datasets with similar objects, one where each object is 50 pixels wide and the other where they are 150 pixels. Each photo is 512x512 for both datasets. These two datasets have the ...
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18 views

Machine Learning algorithm for predicting a user's rating on an item?

I'm trying to build an supervised learning algorithm that deals with the regression problem of predicting a user's rating of a new incoming item based on the user's previous ratings on items. The ...
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1answer
31 views

Hidden Markov Models for Hand Gestures

I am completing a final year project for hand gesture recognition using Hidden Markov Models I have a fair understanding of Hidden Markov Models and how they work using simple examples such as the ...
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1answer
24 views

How can one measure the time dependency of an RNN?

Most of the discussion about RNN and LSTM alludes to the varying ability of different RNNs to capture "long term dependency". However, most demonstrations use generated text to show the ...
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Multi-Interval Discretization of Continuous-Valued Attributes for Classification Learning

I'm trying to figure out Fayyad and Irani (1993) MDLP discretization of continuous variables (here is link to the original paper). I understand how algorithm works, but I have some doubts about first ...
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1answer
54 views

Complete proof of PAC learning of axis-aligned rectangles

I have already read PAC learning of axis-aligned rectangles and understand every other part of the example. From Foundations of Machine Learning by Mohri, 2nd ed., p. 13 (book) or p. 30 (PDF), I am ...
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37 views

Show that if $\mathcal{H}$ is PAC learnable in the standard one-oracle model, then $\mathcal{H}$ is PAC learnable in the two-oracle model

This is a question $9.1$ from Understanding Machine Learning Chapter 3. It goes like this: Consider a variant of the PAC model in which there are two example oracles: one that generates positive ...

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