Questions tagged [machine-learning]
Questions about computer algorithms that automatically discover patterns in data and make good decisions based on them.
1,165
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Learner Algorithm Time & Sample Complexity
Let $X=R^{2}$. Let $u=\left(\frac{\sqrt{3}}{2},-\frac{1}{2}\right),\
w=\left(-\frac{\sqrt{3}}{2},-\frac{1}{2}\right),\ v=\left(0,1\right)$
and $C=H=\left\{h\left(r\right)=\left\{\left(x_{1},x_{2\ }\...
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Cosine distance in a space, and cheating?
I read an example of using cosine distance in RGB space, and it pointed out that (eg.) dark red and light red have a cosine distance (CD) of zero because CD only gives you the angle between vectors ...
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pseudo dimension of the minimum of functions
Suppose a real-valued function class $\mathcal{F}$ with pseudo dimension less than $d$, I am wondering what is the pseudo dimension of the following function class
\begin{equation}
\mathcal{F}_2 = \{\...
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Sensitivity analysis of Multi-Layer Perceptron Neural Networks
I have used Multi-Layer Perceptron Neural Networks to do a binary classification. Now I want to perform a sensitivity analysis. I am planning to follow a similar approach to this paper.
In case the ...
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Calculate the joint probability of two nodes in Markov Random Field
I have a Markov Random Field (MRF) model as described in this picture.
I know the distribution factorizing over the graph is given by $$ p(x_{1:N}) = \frac{1}{Z} \prod\limits_{n=2}^{N} \psi_{n-1, n}(...
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How many model parameters do R-CNN, Fast R-CNN and Faster R-CNN have respectively?
I am making research on object detection and I would like to know the number of parameters these three models obtain.
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K-Modes Clustering with Partially-Overlapping, Variable-Length Data?
I'm working on a project that's attempting to cluster books using machine learning. I'm using the K-Prototypes algorithm for clustering data that has both numerical and class-based data. Under the ...
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How much faster would a semantic segmentation model be with just 2 classes compared to 100 classes?
Let's say I have a semantic segmentation model that distinguishes between 100 classes of objects, and the speed of running the model is 1 image per second.
Now let's say I take the same model ...
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When to stop training a back propagation algorithm based on the MSE?
I have a fully connected neural network that consists of 3 inputs + bias, 4 neuron hidden layer, and 2 layer output, I am using the sigmoid activation function on the hidden layer only and use the ...
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Blackwell-Rao applications to Machine Learning and AI
We learned recently in a graduate statistic course about Blackwell-Rao of an unbiased estimator statistic T; other methods for parameter estimation includes Maximum Likelihood and Method of Moments ...
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Multimodal machine learning dataset fine tuning for binary classification problem
Hello i am new to machine learning, i am working on a multimodal dataset, basically memes dataset, The data consists of an image and an overlay text, i have no clue how to feed a model both of the ...
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Lagrange Multipliers and Hard Margin SVMs
With hard margin support vector machines (SVMs), it suffices to find the critical points of the Lagrangian $L = \frac{1}{2}||\theta||^2 - \sum_{n=1}^{N} \alpha_n (y^{(n)} (\vec{\theta}^T\vec{x}^{(n)} +...
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Which artificial neural network model can I use when trying to predict gene expression?
I need help choosing a model for my data. I have 50 genes that I need to test for their expression levels. I was thinking of implementing either an SVM or a multilayer perceptron model where the ...
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How does TRANSFORMER DECODER WITH MEMORY-COMPRESSED ATTENTION work?
I came across TRANSFORMER DECODER WITH MEMORY-COMPRESSED ATTENTION (T-DMCA) model in the paper "GENERATING WIKIPEDIA BY SUMMARIZING LONG SEQUENCES" (https://arxiv.org/pdf/1801.10198.pdf). ...
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Kitti dataset Pi matrix. Pi is the same with Pi_rect?
Do i understand right that Pi in KITTI calib.txt files is the same with Pi_rect in their paper?: Pi_rect from paper
But what i can't understand it why last column in projection matrix in the paper ...
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Graph algorithm for propagating a feature
I have the following problem:
Given a graph of persons and their relationships.
Suppose I have a classification of the risk of some of those persons.
How can I calculate the classification of the ...
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If all words have the same frequency, is the generated Huffman tree a balanced binary tree?
If all words have the same frequency, is the generated Huffman tree a balanced binary tree? At the same time, is the generated Huffman tree a complete binary tree?
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What is the best way to predict a continuous score based on image characteristics(pixels)?
I have a dataset with 9912 images, what is the best way to train them based on the pixels and features of the images to be able to predict a continuous target ranging from 1 to 100? The goal is to ...
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8
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Definitive source on energy based models
I'm currently working on a thesis based masters on graph generation. For this I need to learn about a variety deep generative approaches, including GANs and autoencoders. One of the approaches I need ...
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Precise definition of Universal Learner in Machine Learning
It is surprising to me that I cannot find a precise definition of universal learner on the internet. I can guess what it should bebut I don't want to make a mistake, therefore I have come here.
Here's ...
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Dependency analysis in a neural network
I was reading [1] about verifying neural networks. $n_{i,r}$ refers to the rth neuron in layer i and all neurons have the ReLU activation function. A neuron $n_{i,r}$ is said to be strictly active if ...
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How a model can handle removed nighttime data in future predictions?
I want to use machine learning models for predicting one day ahead output power. In this model, I would like to remove all nighttime data because they do not make sense in prediction, but the problem ...
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Labeling an image mask as data for object detection?
I am new to machine learning but had a question about a labeling method. If I had the following two images:
Is there a way to use the second image as the label for the first one (i.e. anything in ...
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Linear encoding of a feed forward neural network
I was reading [1] about reachability analysis of a feed forward neural network (FFNN). The paper encodes a FFNN as a linear programming problem. Suppose $x^{(i)}$ is the vector output of the ith layer,...
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37
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Out-sample error for disjoint input spaces
I am trying to understand the fundamentals of Bayesian machine learning and I found an interesting task, which I have tried to solve:
We are in the setting of a binary classification problem with $Y=\{...
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19
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Different results in standard deviation of test set and cross validation
I have used KNN for predicting the output power of solar panels. The results are shown below:
Test Set:
MAE = 0.044
MSE = 0.004
Standard Deviation = 0.272
...
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MAE greater than MSE - is it possible?
I have used KNN for predicting the output power of solar panels. I have done feature scaling based on normalization for all data points. The problem is that the MAE is equal to 0.08, and MSE is equal ...
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Is it really impossible to use K-fold cross validation for time series data?
I would like to know if it is impossible to use K-fold cross-validation for time series of data. It has been discussed that it is not reasonable to predict past from future, but I think this does not ...
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Clarification about RNN encoder-decoder equation
In the paper by Cho et.al., section 2.3 details the equations for the modified LSTM cell in RNN used in the paper's implementation. The equation in question is :
Here, the output of the reset gate (r)...
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Machine learning and test split for time series data
I have used different machine learning algorithms to predict solar panels' power output. There are ten independent features for weather data.
In all models, I set time as an index and have used the ...
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Why is the input of the algorithm in "Linear-Time Self Attention with Codeword Histogram for Efficient Recommendation" a matrix?
My question is about the algorithm in the article Linear-Time Self Attention with Codeword Histogram for Efficient Recommendation, as described in the picture below.
It is written at beginning ...
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What is the difference between discriminative information and diverse information in computer vision?
I am studying deep learning and found a lot of papers in which they tried to distinguish between discriminative information and diverse information.
What disctiminative and diverse information mean? ...
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Understanding halving algorithm in online learning
I am working through "Understanding Machine Learning Theory" by Shai Shalev-Schwartz. In the chapter "Online learning" I came across the halving algorithm, the author uses the ...
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Why word embeddings are compared with cosine distance and not euclidean?
In most articles that compare word embeddings they use cosine distance to determine if words are similar. Why?
I guess that euclidean distance should work too. So, my question is: it doesn't?
And why ...
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How do you detect names that sound similar to English words or phrases?
High school teachers use this Website called Kahoot to post quizzes that are answered live by the students. Students sign in to the quiz and are invited to input a name for themselves, and as you ...
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Bin packing (NP-Complete)
I'm working on a project over Bin packing being NP complete, I understand the full reasoning behind it (algorithmically), but I need to know what's a proper explanation for the Bin packing being NP ...
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Hoeffding's inequality applicability for sample complexity
I am trying to determine some bounds for sample complexity. Suppose we have a bounded loss function $\ell$ and target function $f:\mathcal{X}\to\mathcal{Y}$. Hypothesis $h$ is learned, then the ...
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Function or signal as machine learning model output
I am new to machine learning. I've seen that machine learning models such as ANN or SVM can be used to predict scalar outputs taking scalar inputs.
I am trying to create a model that has a number of ...
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What is the practical difference between "differentiable programming" and existing autograd libaries?
People have recently started talking about "differentiable programming". I have listened to some people talk about this at a philosophical level, but I don't see the practical difference ...
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Uniform convergence of union of hypothesis
Let $H_{1}$ and $H_{2}$ are two hypothesis classes over some domain $X$1.
If both $H_{1}$ and
$H_{2}$ have the uniform convergence property, then do $H_{1}$ U $H_{2}$ have uniform convergence?
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Is it possible to include the unit price in assocation rule mining?
I would like to ask you a question about Assocation Rule Mining. I understand the meaning of a so called rule and the related performance indicators like support, confidence and lift.
However, I'm ...
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Question about machine learning
Hello everyone I am new to the site, I have a question that was in the test and did not understand the parts that are in the question. This question from a test I failed to pass, in a machine learning ...
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prove that 2 collection have the same VC-dimensions
I'm new here on the site, I'm a final year student in computer science.
In a machine learning course, there was a question on a test that I could not understand.
The question goes like this:
Suppose ...
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What type of neural network or machine learning technique would you apply?
I want to predict as many time steps of a variable (X) as possible. The more time steps forecasted, the more successful the solution proposed.
To the best of my knowledge, applying LSTM neural ...
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9
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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 ...
- 139
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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.
