Questions tagged [optimization]

In statistics this refers to selecting an estimator of a parameter by maximizing or minimizing some function of the data. One very common example is choosing an estimator which maximizes the joint density (or mass function) of the observed data referred to as Maximum Likelihood Estimation (MLE).

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Optimizing the Loss Function For Another Metric

Suppose I have a machine learning model which is used to improve the profitability of a business. One of the components of the model is a loss function, say for measuring the success of a ...
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How to do online retraining of model on a single new data point/observation?

I am trying to investigate the effect on performance on old data and new data when a classifier is retrained on only the new observation when it is encountered. The aim is to retrain the classifier on ...
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How to reduce/ optimiize a value to make a prediction model?

I have to make a time prediction model with some features. There is certain optimization value for each rows. by reducing that value I can get optimal prediction ( according to the expectations ) How ...
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finding winning strategy

For a given asset, I have simulations of the price and implied volatility for T periods in N scenarios. Furthermore, assuming that I know the value of the risk-free asset (and the dividend yield), I ...
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Which algorithm should I use to ensure a (near-) optimum order scheduling for a packaging line? [closed]

I'm looking for an algorithm or methodology to solve order scheduling on a packaging line, but I'm struggling to find the right direction/search terms. The simplified version of the problem is as ...
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how to shape a formula pattern by optimization

I have built a formula which has a plot as shown bellow in the photo and matlab code. my formula has 8 "a" and 8 "f" coeffients which decide the shape of the plot. How can i do an ...
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Why the error between the measured data and model data is not minimizing in Python?

I want to fit the non-linear experimental data with the model function by estimating some parameters in the function. The model function I have is: ...
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Can I run this job quicker for GridSearchCV?

I am using GridSearchCV for optimising my predictions and its been 5 hours now that the process is running. I am running a fairly large dataset and I am afraid I ...
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Question on hinge loss for GANs

I'm currently experiencing some difficulty with the hinge loss optimizer for GANs. In the equation below, the discriminator is looking to minimize $L_D$ and the ...
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Machine learning with constraint on outputs

I'm experimenting with a 3D pose estimation model that predicts 3D keypoints, given 2D keypoints as input. Since the distance between these predicted joints in 3D is known and constant (we know the ...
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Memorization in deep neural networks, random vs. properly labelled datasets

From about 19:20 in the video here: https://www.youtube.com/watch?v=IHZwWFHWa-w it shows the difference in value of the cost function for randomly labelled data vs. properly labelled data. What do ...
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How does bayesian optimization with gaussian processes work?

Could someone explain in simple words what are gaussian processes how does bayesian optimization work and their combination?
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How does Keras optimization for a network with multiple outputs

I currently have a neural network that takes in 3 numbers as inputs and outputs 3 numbers. I've attached a picture of the network below and my code is accessible through the following link: [Google ...
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using Reinforcement learning for binary classification

I want to build an agent for binary classification. I have a large dataset with two label (0 and 1). I want to build an agent to predict labels. I build a deep model and now I want to build an agent. ...
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Optimise for the sum of regression predictions?

I'm building a machine learning model to forecast the number of students on a course at a University. I'm currently optimising for MAE for each sample (i.e. a ...
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Multiclass data redistribution

I want to redistribute the data in classes according to new proportions and wonder what is the optimal way to do it. For example I have ...
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GAN model with different optimization functions

Building GAN model contains the following steps: Build generator model, and choose ...
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Step size finds by quadratic fitting in steepest descent

I have a function $f=(1-x_1)^2 + (x_2-(x_1^2))^2$ and initial point $[0,5]$. I wonder how I will find step size by quadratic fitting using the (e.g. $0.01$) value in Steepest Descent with Matlab. To ...
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How can I optimise/parallelize my neural network code?

I have a neural network with 784 inputs, 30 hidden neurons and 10 output neurons. The main performance issue is when backpropagating. Currently it takes around 0.1 seconds for one iteration of ...
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Sine curve fitting

I want to fit a a * abs(sin(b*x - c)) + d function for each of the following data. In most of the cases I'm able to get decent accuracy. But for some cases, I'm not ...
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Hyper parameters (window size and vector dimensions) tuning in word2vec using Grey Wolf Optimization

Using Grey wolf Optimization, I want to calculate optimal values of two hyper parameters: context window size and embedding size (vector dimensions) for word2vec skipgram model used for word embedding....
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Determining the right box size for packaging

I was given a very challenging problem at a logistics company and I would appreciate your help. My company ships products from a clothing brand from the warehouse to final e-commerce client. The ...
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ADAM optimizer yields sub-optimal results

I've been writing my own neural network from scratch to get a better understanding of how they work (using MATLAB initially, but plan to port it to C++ afterwards). One major problem for me has been ...
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How does fusing operations lower accuracy for machine learning models?

In this talk the speaker Sachin Joglekar mentions that it's important to consider tradeoffs when choosing delegates for optimizing Tensorflow Lite. One of the tradeoffs he mentions at 10:14 is that ...
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Problem with elastic constraints in PuLP

(This is my first question on Stack Exchange) I am working on a production allocation problem, whereby sales orders have to be allocated over three production plants. I am using PuLP in Python, and ...
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Optimal points of $f(x,y)=x^2 + y^2 + \beta xy + x + 2y$

I am self-learning basic optimization theory and algorithms from "An Introduction to Optimization" by Chong and Zak. I would like someone to verify my solution to this problem, on finding ...
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Is it okay to train Triplet Loss where the anchor and the positive are the same?

Triplet loss roughly defined as total of$$ max (- distance(Anchor,Negative) + distance(Anchor,Positive) +margin,0)$$ I'm working with triplets data, and it turns out that some triplets(just small ...
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How to optimize AUPRC for imbalanced data given a precision or recall bias?

My general understanding is that when optimizing a model in an imbalanced class case with a small preferred target class one should optimize first for a model with the best AUPRC (assuming one doesn't ...
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Model selection for multiple groups to maximize overall f1 score

Model 1 Model 2 .. Model m Group 1 tp11/act1/pred11 .. .. Group 2 tp21/act2/pred21 .. .. .. .. .. .. .. Group n tpn1/actn/predn1 .. tpnm/actn/prednm I have a multiple groups model selection for ...
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Identifying subset of feature set to represent remaining features using pca or any other techniques

How can you use PCA to identify a subset of feature set to represent remaining features in a data set? Suppose there are 10 features given by F={ f1,f2......f10}. How to identify a subset of F such ...
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Qunatify total time saved by prioritizing tasks based on the failure rate probability of each task

I am trying to solve a problem where I am trying to prioritize the tasks in a job based on the failure rates of each task. For ex: ...
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Cluster fusion techniques for global optimal solution

Suppose you have a huge data set. You divide that data set into N number of blocks. Each block is then clustered into M blocks (using any clustering algorithms like K means). Now you have N local ...
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BERT MLM overfitting [closed]

We are training the BERT model on masked language modeling task for the Russian Language. Our dataset consists of 60 mln texts with (128 tokens for each text) from online social networks, ...
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Evolutionary search mutation range

Im currently writing an evolutionary program that has the task to optimize a weight set for a neural network for a specific and well defined environment. It is performing excellently but i am getting ...
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Ant colony optimization for clustering [closed]

What do you mean by applying ant colony optimization (ACO) to clustering? What is the output one would get after it? Could you explain it using a two dimesional data set which is clustered into 3 ...
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avoiding premature convergence with neural networks (EA's)

I am currently writing a program that would be able to play snake on an 25*25 grid. It works by optimizing a set of weights of 300 different solutions (each solution would be a different neural ...
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Custom thresholds on categorical classification

When assessing a binary classification task, it is possible to search for particular threshold in order to have better score on some metrics (f1,recall,etc) through numerous methods. Unfortunately, it ...
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Why is my accuracy 0 on the first epoch in continuous training on MNIST

I'm trying an experiment where I first train my model on MNIST labels [0-4], and then I freeze the first conv layers and continue training my model on labels [5-9]. When I dont re-initialize my Fully ...
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Would a neural network trained on extracted features have the same accuracy as a full network with frozen layers?

Let's say that I train two neural networks on the exact same dataset. The first network is a VGG19 model with frozen convolutional layers so only the top dense ...
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Do I load all files at once or one at a time?

I currently have $1700+$ CSV files. Each of them is in the same format and structure, give or take a row or possibly a column at the end. Each CSV is $\approx 3.8$ MB. I need to perform a ...
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Loss function for points inside polygon

I am trying to optimize some parameters that used to transform 2d points from a place to another (you may think of that as rotation & translation parameter for simplicity) The parameters are ...
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How to maximize a log linear regression equation satisfying a constraint?

I have a log linear equation of the form $y = w_1(\log{X1}) + w_2(\log{X2}) + ... + w_n(\log{Xn})$. How can I find the value of X's that maximize the value of y subject to a constraint $(X_1+X_2+...+...
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Curve fitting (or other techniques) for revenue and price optimization

My question is as follows: with historical data we can model the relationship between discounts and sales (number of sold units). So we can address the question "how are sales boosted by ...
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37 views

What method/algorithm for constrained multi-target regression

I am working with three dimensional measurement data and want to model them using a multivariate linear regression. I have already implemented a simple gradient descent algorithm to solve the classic ...
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Finding the dual to an optimization problem on an unsupervised dataset [closed]

We consider the unsupervised dataset $x_1,..x_N \in R^d$ and the optimization problem: $$min_w \,\frac{1}{2}{\left\lVert w \right\rVert}^2,$$ subject to constraints:$$\forall_{i=1}^N: \phi(x_i)^Tw\...
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Need help to understand backpropagation for gated recurrent units (GRU)

I'm stuck regarding the implementation of backpropagation in a binary classification task using a GRU. I wanted to know if someone could tell me how to proceed. I was able to understand how BP works ...
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105 views

Terminology to distinguish between ML methods and optimization methods (PSO, ACO..)

I am currently writing a scientific thesis which consists of two parts. In the first part I am building ML models with neural networks, support vectors etc. and the second part is about finding global ...
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Optimize Yahoo Finance Code for Analysis [closed]

I am trying to analyze a number of companies using financial data I gathered from Yahoo Finance. I am also using the yfinance API to get some more details about the company using functions. Since I am ...
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Gradient descent around optimal loss surface

All the loss surface used in examples have some of bowl shape that decrease drastically far from the optimal and decrease slowly around the optimal flat point. My questions are: Has all the loss ...
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Notation for anti-optimal

What's the notation for the worst element/solution? The best "something" can be denoted with *, i.e.: $R^* = R_{best}$ $R^? = R_{worst}$

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