Questions tagged [machine-learning]
Questions about computer algorithms that automatically discover patterns in data and make good decisions based on them.
1,050
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15 views
Trying to figure out the best way to approach this problem with Computer Vision
Newbie to CV here so sorry of this is basic. Here's the deal, I have a program that I run many times. and each run I produce a screenshot. I need to compare screenshots from N-1 and N runs and make ...
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0answers
14 views
AI algorithm for matching existing commodities in kitchen with recipes
We have an idea about helping people make recipes from what they have in their pantry and refrigerator using AI. So for this idea, we're thinking the fridge takes a picture of the groceries when they ...
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6 views
Citation Graph prediction
If I have reference section of a paper, with how much probability can I predict one of the authors of that paper ?
Any recommendations on suitable algorithm to build a model are appreciated.
Also how ...
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0answers
6 views
Prophet Model in Batch Implementation
I am newby at Prophet model. I was wondering Prophet uses stochastic or batch approach while in training. If it uses stochastic that means there is nothing to do convert and compute mini batch ...
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1answer
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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2answers
27 views
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 ...
1
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1answer
21 views
“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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13 views
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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1answer
36 views
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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0answers
60 views
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
37 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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1answer
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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9 views
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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1answer
15 views
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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0answers
35 views
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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27 views
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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14 views
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.ćTo do so, ...
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22 views
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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0answers
15 views
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 ...
1
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1answer
19 views
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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0answers
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
17 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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0answers
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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13 views
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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0answers
11 views
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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1answer
43 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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1answer
60 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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1answer
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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2answers
21 views
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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1answer
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 Ļµ > 0, it is NP-hard ...
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1answer
31 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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1answer
63 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 $P^m$
$$
: L_S(A(S)) ā L_P (A(S))| = 1
$$
Now I wanna prove for ...
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13 views
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 ...
0
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1answer
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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25 views
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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14 views
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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0answers
20 views
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 ...
2
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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 ...
0
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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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0answers
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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0answers
13 views
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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0answers
18 views
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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15 views
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 ...
2
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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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0answers
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 ...
1
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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 ...
