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

Hand Landmark Coordinate Neural Network Not Converging

I'm currently trying to train a custom model with tensorflow to detect 17 landmarks/keypoints on each of 2 hands shown in an image (fingertips, first knuckles, bottom knuckles, wrist, and palm), for ...
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RMSProp Momentum and Decay

I'm making an application of MobileNetV2 and according to their article: We train our models using TensorFlow. We use the standard RMSPropOptimizer with both decay and momentum set to 0.9. We use ...
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what do i need to consider writing a python script that uses a pre-trained model with new incoming data

I have completed and saved(with joblib) a trained model to do with detecting messages that exerts pressure. I understand that for me to use the model I would need to use joblib again to deploy my ...
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How to calculate the prior covariance matrices in "Interactive Text Ranking with Bayesian Optimization"? (A Gaussian Process used for Q&A)

My question is about the article Interactive Text Ranking with Bayesian Optimization A Case Study on Community QA and Summarization, which uses Stochastic Variational Inference described in the paper ...
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Explain why there is no need to invert a Covariance Matrix in this Gaussian Process

My question is about the article Scalable Bayesian preference learning for crowds. The paper describes the use of Stochastic Variational Inference (SVI) for solving the problem called Preference ...
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How to write code for levy flight in cuckoo search

I want to write levy flight random number distribution code for cuckoo search optimization. So how to select randomly two instances from set of instances by levy flight.
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19 views

Proof of Calculating VC-Dimensions

I still have some doubts for finding the VC-dimension. Suppose $\mathcal{H}$ has VC-dimension $n$. This is the process of how I think about it: (1) Show that there is a set of $n$ points that can be ...
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28 views

PAC Learnability of Infinite Hypothesis Classes

Is it true that for a finite or a countably infinite hypothesis class $\mathcal{H}$, then it is going to be PAC-learnable (and vice-versa)? And what about if we change the cardinality of the ...
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What is the best learning to hashing for embedding points in a Vector Space in Hamming Space?

I have a cloud of points in $\mathbb{R}^n$ and I want to embed them in Hamming Space. One possible solution is for example found in Inductive Hashing on Manifolds. The problem is: I need an extremely ...
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Learnability of singleton in realizable case

I am required to show that the class of singletons $H_{sing}$ is learnable in the realizable case (without invoking the VC-dimension). $H_{sing}$ is defined as $H_{sing} := \{h \in \{0, 1\}^X : |\{x \...
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Random initialization of weights

I have trained a neural network using a train and a validation dataset.I used the validation dataset for hyperparameter and architecture optimization.I split the dataset in the exact same way each ...
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"Hot Word Detection", bur for different applications

I have been looking in detecting a specific rhythm/pattern within the temporal domain for a time-series signal. For this purpose, how "Wake Up" words work for devices like Alexa have gained ...
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Are the weights between hidden layers changed in backwards propogation? If so, how

If so, I don't understand how, as a large part of back propogation is knowing what the 'real' answer is in comparison to 'predicted' answer. With 1 neuron in a hidden layer, we do not know the 'real ...
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Difference between C-Index and Spearman correlation

Suppose I have a list that reflects the priority of web pages for recrawling: l1 = [3, 2, 1, 4, 2, 5] Now, I have tried to estimate the priorities with two ...
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1answer
43 views

VCdim of concentric circles

I have researched this topic in the last time, but no usefull results for me. So I'm here and I please you to help me with the following problem: What is $VCdim$($\mathcal{H}$), where $\mathcal{H}$ is ...
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104 views

Learn a system of linear inequalities given solutions

Instead of finding a solution to a system of linear inequalities (Ax + b >= 0), I want to find any system of linear inequalities that satisfy a set of feasible ...
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35 views

Why is quadratic programming used to the solve the support vector machine optimization problem instead of the analytic approach?

(Readers familiar with the mathematical framework of support vector machines may skip to "The problem") https://youtu.be/eHsErlPJWUU This is a lecture video by Abu Mostafa on support vector ...
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Best way to deal with strongly correlated variables in a prediction problem?

I am doing a prediction assignment as part of a machine learning course using loans data. I have just done some exploratory data analysis on my dataset of just over 9000 rows. There are 11 variables ...
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Predicting continuous variables using image and text input to neural network

I am looking to create a neural network architecture that takes two kinds of inputs: image and text, and outputs a predicted continuous variable. More specifically, I will have multiple images of a ...
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Does it make sense to use Bayesian Network to understand feature correlation of clusters created with K-means?

My project idea is to create clusters of typical rooms for hotel customers, indicate which rooms are similar to the one they are looking for and let them understand why they are conceptually similar. ...
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How should I create a word-embedding an NLP model recognizing HTML elements?

I'm currently doing a small-time project where I have to deliver a model which can classify specific elements on a web-page using the HTML code. For this, I have considered using the HTML tags for ...
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1answer
27 views

Why is $\mathcal{D}^m(\{S:L_{(\mathcal{D},f)}(A(S))\gt \epsilon\})\leq \mathcal{D}^m\left(\bigcup^4_{i=1}F_i\right)$ true?

I am studying the book "Understanding Machine Learning: From Theory to Algorithms". I am struggling to understand the solution to exercise 3 (2) on page 41. Exercise: An axis aligned ...
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45 views

Distinguish supervised learning , unsupervised learning and reinforcement learning

AlphaZero is a computer program that was originally built to master the games of chess, shogi and go. It was trained solely via "self-play", in parallel, with no access to opening books or ...
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Merge N number of euclidean distance matrices to get an overall single euclidean distance matrix

I want to find out the aggregated euclidean distance of a big dataset D comprising of x and y cordinates where the data set is divided into N sub dataset where 1st sub dataset contains 1 to kth ...
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1answer
15 views

What if the samples in the dataset are fairly naturally similar to each other, would that be considered as data redundancy?

I am working on building ML/DL solution for a problem where that data is considered, naturally similar and I am worried if that would be considered as data redundancy. My question is, is that so? and ...
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Why can we apply standard matrix operations in data matrix but not in record data?

Tan,Steinbech,Kumar book says-: A data matrix is a variation of record data, but because it consists of numeric attributes,standard matrix operation can be applied to transform and manipulate the ...
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What do we mean by permissible transformations in types of attributes-:nominal,ordinal,interval,ratio? [closed]

I am studying data mining and I stumbled upon types of attributes. They are Nominal Ordinal Interval Ratio Data mining book by Tan,Steinbech,Kumar says Permissible transformations for-: nominal-:...
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21 views

How to cover a surface with a predefined set of objects

I'm making a program that's supposed to be able to find pieces of wood in a dataset to cover a surface. For now I'm focusing on parallelepipedic shapes to simplify the problem (eventually I'd like it ...
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Ratio of intra-class scatter by inter-class scatter is getting minimised by linear discrimination process

I am optimising projection matrix P using Fisher linear discrimination formula maximise following with P J=N*tr(trnspse(P).SB.trnspse(SB).P) / c * tr(trnspose(P).SW.transpose(SW).P) As per theory, P ...
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1answer
65 views

A confidence interval algorithm for Disagreement coefficient

My question has to do with the disagreement coefficient in active learning. I've been trying to solve the following question, where I need an algorithm to derive a confidence interval for $\theta$, ...
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Could someone explain the algorithm from this paper? (Thank you) [closed]

Trying to get a fair understanding of our artificial immune systems. To do this I’ve been reviewing this paper, but the algorithm and mathematics is over my head, could someone explain the below to me ...
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What are the job names for researching neural networks & deep learning?

I am a student who wishes to research neural networks (ANN, CNN, RNN) and deep learning, write papers on those topics, and actively participate in forums like CVPR. My question is: Which professions ...
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What is the primary reference for the observation/discussion of how neural networks struggle with ambiguous training datasets?

It is known that neural networks, such as convolutional neural networks, struggle with pattern recognition if training sets contain ambiguities (i.e. several labels can correspond to one and the same ...
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What is the point of Transforms in Pytorch when loading Dataset?

I am not sure what the point of the data augmentations in PyTorch when loading images. Specifically, I am talking about this: ...
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1answer
187 views

How does the TEPS benchmark work and why is it relevant to real world problems?

Graph500 is a competition for supercomputers that uses a different benchmark "Traversed Edges Per Second", which is supposed to measure some notion of the communication bandwidth ability of ...
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Question of about Boltzmann machine implementation

I would like to implement Boltzmann machine with two hidden and two visible units. The four possible hidden units configuration are $(0,0), (0,1), (1,0), (1,1)$, and their probability distribution is $...
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Can we supervise on the hidden states of RNN?

I'm trying to generate some history-dependent model with machine learning, whose underline physical model has a clear definition of its "internal state variable" (a state derived from ...
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Learning algorithms- difference between a learner (the algorithm) having continuous access to the samples (oracle) vs getting all at start

Is there any fundamental difference between learning algorithms e.g. variants of PAC which have continuous access to examples on which to train (i.e. these are obtained as the algorithm runs, when ...
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Using Restricted Boltzmann Machines for clustering data

I want to use RBMs as a clustering model and the idea is to use an RBM for clustering a 16 class clustering problem with 4 nodes in the hidden layer. The clustering is done by updating the hidden ...
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29 views

Describing a consistent learner

Let $X=R^3$. Let $C=H=\{h(a,b,c)=\{(x,y,z) |x|\leq a,|y|\leq b, |z|\leq c\}, a,b,c\in R_+\}$ the set of all origin centered boxes. Describe a polynomial sample complexity algorithm that learns $C$ ...
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77 views

Why does it take O(n!) time to specify a canonical ordering for learning flatten adjacency matrices/graphs?

I was reading a paper for learning graphs (paper is GraphRNN) and it says in section 2.2 (emphasis by me): Vector-representation based models. One naive approach would be to represent G by flattening ...
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1answer
19 views

How many pixels support each neuron in multi-layer CNN?

I'm studying for a computer vision module and I'm on the deep learning topic, in one past paper we have the following question: Given that a convolutional neural network has five convolution layers (...
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Applications of derivative only, zeroth-order free optimization

I understand what is derivative-free optimization, and I am thinking a similar problem where the function $f$ we are optimizing is unknown and the only information we can acquire is the derivative. In ...
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34 views

What are open-loop and closed-loop modes of neural networks?

I came across the following line in the book ‘Deep Learning (Ian Goodfellow) 10.2.1, pg 374; The disadvantage of strict teacher forcing arises if the network is going to be later used in an open-loop ...
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23 views

What is the relation between the compatibile features and the state features in Actor Critic Algorithm?

According to Actor-Critic algorithm, $\psi_{\theta}=\nabla_{\theta}\ln \mu_{\theta}(s, a)$ where $\mu_{\theta}(s, a)$ is the policy followed by the actor and $\psi_\theta$ is the compatibile features ...
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29 views

Find the exactly correct separating hyperplane of SVM when the data is not perfectly linearly separable

I am thinking about the following case where the data in region 1 is always positive and the data in region 2 is always negative, but the data in region 3 can be both positive and negative. Are there ...
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80 views

How to transform an Abstract Syntax Tree (AST) to an Abstract Binding Tree (ABT)? (for machine learning fo theorem proving)

I was reading the HOList paper that applies Graph Neural Networks (GNNs) to the HOL Light (HOList) data set and benchmark for ML for theorem proving. They describe their results etc but there is no ...
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20 views

Reference selection for rating assignment based on pair comparison

Background: a set of 300 images are prepared, randomly pair compared with 60 other images, assigned a rating (from 1-star to 5-star) based on the pair comparison score (+1 if wins a pair comparison ...
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Sequence prediction with known information

recently Hamas has shot a lot of rockets to Israeli cities. I found a large database containing thousands of entries from the past 3 days. The database is a large list of triplets in the form of $(...
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1answer
86 views

Representing abstract syntax tree as a graph

Does it make sense to represent an AST as a graph? How can one achieve a mapping between ASTs and graphs that preserves both semantic and syntactic properties of source code? The goal and application ...

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