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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Objective function

I want to learn how to write objective functions for any problem or real-life action(not mathematical problems) can anyone suggest a good source? On online I am mostly finding objective functions for ...
Star Lord's user avatar
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How exactly does minimizing the L2 norm of w in SVR affect the model's ability to fit the data?

I have a solid grasp on why we minimize the L2 norm of the weight vector ( w ) in Support Vector Machines (SVM) for classification problems — it maximizes the margin between classes and helps the ...
dedman2000's user avatar
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Upper bound via standard manipulation in proof of semi-private learning

I have been reading a paper on private learning [1]. In the proof of lemma 3.3. they claim that $$ 2\left(\frac{2e n_\text{pub}}{d}\right)^{2d}e^{-\alpha n_\text{pub}/4} $$ is upper bounded by $\beta$ ...
TheCollegeStudent's user avatar
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Q-learning table efficiency

So I am trying to create a Q-learning algorithm to solve simple games, starting with tic-tac-toe. I would like to do so without completely eating away my memory, but all the examples online create a 2 ...
Clement Genninasca's user avatar
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PAC-learning framework: Why the sample size must also be polynomial if the full sample is received by the algorithm

On page 11 in the book Foundation of Machine Learning, 2nd edition MIT press, the authors wrote: Definition 2.3 (PAC-learning) A concept class $C$ is said to be PAC-learnable if there exists an ...
Tran Khanh's user avatar
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Incompresensible about $w$ $x$+ $b$ = 0

I don't actually understand the meaning of $w$$x$ + $b$ = 0 when it is defined in support vector machine. In my own understanding, in order for the equation to be true, the hyperplane would always ...
ABC's user avatar
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Impact of label flipping on ROC-AUC score

I was exploring a problem of label flipping in the target column: Problem: I have a data frame with just two columns: Predicted probability | Target. Target column is binary (contains only 0 and 1) ---...
Grigori's user avatar
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Finding an algorithm EF[1,1] and PO division for more than two agents

From this research paper I want to write an algorithm for finding envy-freeness(EF) and Pareto optimality(PO) division for more than two agents. We consider the problem of fairly and efficiently ...
user19121278's user avatar
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Transductive Information Maximization vs classification with feature embedding in higher dimensional spaces?

Recent research work has shown that transductive learning/inference outperforms standard methods that were used before, where people embed features in a high dimensional space and then use the ...
Sandra's user avatar
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Latent variable model from measure theory perspective

It's common in machine learning papers to see things like $p(x,z|\theta)$ or $p(x|z)$. Where $x$ is usually the data vector, $z$ the latent vector and $\theta$ the model parameter, like network ...
SecondOrderConfusion's user avatar
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How to distinguish between Unrepresentative Train Dataset and minimal overfitting from a learning c

Is this a minimal overfitting or like unpresensitive train dataset? However, I read it on the net but still have a problem with the graph! And then I read the following text on the net and again I ...
Amirreza Hashemi's user avatar
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Dilated LSTM vs LSTM

I'm currently reading a paper for a literature review related to NLP and its research employs a dilated LSTM model. What is the difference between this and a regular LSTM, or more specifically what ...
paul lacher's user avatar
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29 views

Question about data to train an machine learning IA

I'm trying to create a machine learning program to predict the winner of UFC fights. I want to train my AI with data from previous matches, but I have encountered a problem. I wonder if the algorithm ...
BlizZ's user avatar
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DeepMind Alphadev: How did it use Reinforcement Learning to reduce the search space?

Google DeepMind recently published a new paper which describes how they used a reinforcement learning to discover faster sorting algorithms. A summary of the paper is here and the paper is here. It ...
equis's user avatar
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What is currently the best theoretical book (or notes) about Convolutional Neural Networks?

I have a degree in maths and i am interested in learning about Convolutional Neural Networks from a mathematical/ theory point of view. Can someone point me towards some resource. I already have a ...
PhysicsQuestion's user avatar
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Solving constrained optimization problem using PyTorch: Minimizing L1 norm of $\vec{x}$ subject to $\vec{x} = \mathbb{A^{-1}}\vec{y}$

My goal is to solve the above-constrained minimization problem where my vector to be optimized is x. The matrix A and the vector ...
Dixshant s's user avatar
1 vote
1 answer
163 views

Why GPT model is a higher order hidden markov model

I have read the GPT-1 paper, and my understanding is that it works as follows: $U$ is input tokens, $h_0=UW_e+W_p$, $h_i=\text{transformer_block}(h_{i-1})$ and the output is a probability vector $P(u)=...
123's user avatar
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how Is Convergence of machine learning bounded O(n)?

All charts of machine learning performance (y-axis:accuracy 0.0-1.0) across epochs have the below shape. Is there any research that explain how this convergence is bounded O(n) where n is the number ...
Koenig Lear's user avatar
1 vote
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Transductive Learning vs Inductive Learning in Machine Learning

Several recent research work has shown that transductive learning/inference outperforms inductive learning/inference during classification problems. This has been found in few-shot learning, other ...
Sandra's user avatar
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How to calculate the growth function of a hypothesis class?

I have this hypothesis class: H = {ha : R → {0, 1} | a > 0, a ∈ R, where ha(x) = 1−a,a = { 1, x ∈ [−a, a] 0, x ̸ ∈ [−a, a] } I need to compute the growth function for m>= 0. So I think that this ...
anonymus's user avatar
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1 answer
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meaning behind activation function

I have been recently thinking about activation functions and the explainability. For sigmoid and tanh activation functions, I am thinking of them to be similar to logistic regression as the output of ...
zhan danning's user avatar
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2 answers
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ML model to pick to classify data with inputs as an array of strings?

I have a medical dataset, which is something like this ...
Ashrjz's user avatar
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Create a simple Neural Network of n layers in python from scratch with numpy to solve XOR example problem using Batch Gradient Descent

I'm a young programmer that was interested by machine learning. I watched videos and read articles about the theory behind simple neural networks. However, I can't manage to set it up correctly. I've ...
NolanGio's user avatar
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How to show that an algorithm is not fair?

Algorithm fairness is the field of research aimed at understanding and correcting biases like these. It is at the intersection of machine learning and ethics. Specifically, the field includes: ...
Shi's user avatar
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Analyzing network architecture with TDA

I'm doing Neural Architecture Search (NAS) by varying the number of layers and neurons per layer for a neural network (connections are feed-forward throughout), and then training it on a fixed task to ...
user314159's user avatar
1 vote
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PAC Learning LTFs with random classification noise and membership query

How would one design an algorithm to PAC learn linear threshold functions with random classification noise using membership queries? More formally, the learner has access to unlabeled examples from an ...
envyul's user avatar
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1 answer
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How can a Machine Learning model predict this classification problem?

I am pretty new to ML and have a basic but fundamental question. Let’s imagine we want to create a simple Sentiment Analysis model using Machine Learning not Deep Learning algorithms, so we need to ...
Z Bokaee's user avatar
1 vote
0 answers
60 views

Initialization of embedding space value for VQ-VAE

I am trying to study a research paper about VQ-VAE: Neural Discrete Representation Learning, Aaron van den Oord, Oriol Vinyals, Koray Kavukcuoglu, NeurIPS 2017. I have difficulty to understand the ...
ryan chandra's user avatar
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1 answer
45 views

Difference between paradigm and Algorithm in Machine Learning

Give a class $\mathcal{H}$ of predictors from the set X to $\{0,1\}$. Here each $h \in \mathcal{H}$ is a function from $h: X \longrightarrow \{0,1\}$. The Empirical Risk Minimization is defined as $$...
Shi's user avatar
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Question about the proof for the sample complexity of axis-aligned rectangles

The classical proof for the sample complexity of the hypothesis class of axis-aligned rectangles usually begins by stating that our $A(S) \subset R^*$, where $R^*$ is the target function. My only ...
Dragoș Constantin's user avatar
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In the next ten years, what modifications to hardware architecture do you anticipate being made to enhance machine learning performance?

How do you believe prominent deep learning ASIC makers such as Nvidia and Google will alter their hardware design over the next decade to meet the exponentially expanding need for extra computing to ...
matty 's user avatar
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Role of State Dynamics Target Network in DDPG

I am trying to create a variant of DDPG in MATLAB that has no action-value $\langle Q \rangle$ net, but that instead works with networks $\langle V \rangle, \langle f \rangle, \langle r \rangle$, and ...
Vera Leighton 's user avatar
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Bellmann Error with Time Step

I define the return $G$ as the discrete time integral of the reward $G = \Delta t \sum_{t = 0, ..., T}r_t$. In supposing $\Delta t = 1$ throughout, my instructor wrote the following formula for the ...
Vera Leighton 's user avatar
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Facial Recognition

I need an algorithm that can do facial recognition in a video based on a training set. For any faces detected, it should give an output as how much the face matches with the faces in the training set. ...
Arinjoy Pramanik's user avatar
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25 views

If the data that I input for locality sensitive hashing is sensitive, should its resulting hash also be considered sensitive?

Is it correct to assume that if the input that I hash is sensitive, that I should also consider the locality-sensitive hash generated for that input to be sensitive? I presume that, if an attacker has ...
Pierre Duluth's user avatar
1 vote
0 answers
54 views

Draw the decision boundary of an neural network

I'm really confused when it comes to what the difference between bias and threshold is. I have read that they are basically the same thing and that they serve the same purpose. Being on opposite sides ...
kim120's user avatar
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1 vote
1 answer
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Resources to learn NLP

I am an undergraduate student in mathematics. I have a fair bit of experience with deep learning in computer vision research and am willing to dabble into NLP. I hope that things won't be very ...
The Limit Does Not Exist's user avatar
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0 answers
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How to get started with computational research after a PhD in Physics?

I have a PhD in theoretical physics, where I had worked on mathematical models of hydrodynamics around compact objects. I have basic knowledge of programming in C/C++ and Python. Currently, I am more ...
Richard's user avatar
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1 answer
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How sparsity term in loss function for sparse autoencoder is making hidden units inactive?

I am working on a Sparse Autoencoder but Andrew NG's notes are hard to understand. My question is about the following equation: Loss Function. In sparse autoencoder, the goal is to inactive some ...
p200401Samuel's user avatar
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21 views

Dynamic Bandwidth Parameter for Locally Weighted Linear Regression (LWLR)

When performing LWLR we set the weight based on $w^{(i)} = e^{\dfrac{(x^{(i)}-x)^2}{2\tau^2}}$ where $x$ is the input for our prediction model. Given two x's - $x_1 and x_2$ s.t. $x_1 != x_2$ and $| ...
Izak's user avatar
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2 votes
3 answers
167 views

Does ChatGPT use specific sub-programs

I have had a somewhat hard time trying to understand how ChatGPT can "solve" some tasks that cannot be entirely cast as language-model-based rephrasing of textual subsets of the internet ...
Radio Controlled's user avatar
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1 answer
4k views

What are the 175 billion parameters used in the GPT-3 language model?

I am currently working my way through Language Models are Few-Shot Learners , the initial 75-page paper about GPT-3, the language learning model spawning off into ChatGTP. In it, they mention several ...
Lance's user avatar
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Weighted-Graph Datasets

I am searching for datasets to evaluate an algorithm designed for tasks such as node-classification (edge-prediction, etc.) on weighted and potentially directed graphs. The Stanford Network Analysis ...
Qualearn's user avatar
2 votes
1 answer
60 views

System Identification vs Machine Learning for dynamic system modelling

So I found another discussion regarding this, but the answers did not fully separate the differenced between SID and ML. Hopefully a discussion here can shed some light on some larger differences both ...
bullfighter's user avatar
1 vote
0 answers
50 views

Details about KNN based background segmentation

I build a python script which uses OpenCV implementation of KNN Backgroud Segmentation/Remover. I know the basics of how KNN works, but not how the background segmentation works. For the MOG algorithm ...
Standard's user avatar
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-1 votes
1 answer
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Convolutional neural network for non-image data

I am working on a project for the prediction of preeclampsia, and one of the algorithms to be used is the convolutional neural network. I am a beginner in machine learning, and I am struggling to ...
HANEEN Mohammed's user avatar
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0 answers
22 views

How do you prove a presence of GAN generated samples being exactly (or almost exactly) identical to real observations?

Suppose that $X\in\mathcal{X}$ is data in abstract space and $Z\in\mathcal{Z}$ is random noise vectors in latent space over a defined prior $P(Z)$ (e.g., Gaussian). Then, let $G$ and $D$ denote ...
auckydocky's user avatar
1 vote
0 answers
92 views

grouping/clustering of lines using Hough transform

I am new to Hough transform, though I have some basic idea about it. I am currently trying to fit the best line to a cluster of points $\left(x_i, y_i\right), i = 1,2,\cdots , N$, where there are ...
user146290's user avatar
1 vote
1 answer
42 views

Machine Learning algorithm to learn submodular set functions

I'm looking for some machine learning algorithm to train on data that are sampled from some submodular set function and I want the learned model predictions also obey submodularity. For example linear ...
Arash Jamshidi's user avatar
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1 answer
83 views

How can I find a Stable Diffusion program?

Well, I know that I'm going to ask too much. So, I really want to ask you a totally (powerful (!)) free completely off-line code to generate prompt-based images like midjourney. I want to run with my ...
M.N.Raia's user avatar
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