Questions tagged [algorithm-request]

Use this tag when you're looking for an algorithm (in the context of artificial intelligence) to solve your specific problem.

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Is there a standardized method to train a reinforcement learning NN by demonstration?

I'm less familiar with reinforcement learning compared to other neural network learning approaches, so I'm unaware of anything exactly like what I want for an approach. I'm wondering if there are any ...
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20 views

What object detection algorithm is the best for my particular problem?

I am trying to write a program to put a bounding box around dead fish, and not the live ones, in a video. I have minimal data (~5k frames and ~7k objects in total ) and it is VERY low quality (poor ...
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Determining a policy to play a game of chance

I'm trying to optimize the expected return from a game of chance, but have quickly realized the problem outclasses the introductory AI course I took in college years ago. I would appreciate any ...
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27 views

Are there more optimization methods like GAE for PPO [closed]

I posted about this earlier, but got the suggestion to separate the questions. I'm currently trying to "solve" the OpenAI gym "Humanoid" environment. To improve the training ...
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1 vote
1 answer
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Which RL algorithm should I use to learn an optimal weight vector?

What is the best practice in order to learn the optimal weight vector $W^*$? By optimal I mean the weights that will produce the agent with the highest win-rate. I have an agent that plays a ...
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How to solve a reinforcement learning problem with a stochastic reward function?

In a discrete time system, an environment has an unknown reward probability $p(r|s,a)$. However, the transition probability $p(s'\mid s,a)$ is deterministic. In my case, the reward for the same action ...
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3 votes
1 answer
49 views

Is there any variant of perceptron convergence algorithm that ensures uniqueness?

The perceptron convergence algorithm given below ensures the convergence of weights of the perceptron provided enough data points and iterations. Although it ensures convergence by finally getting a ...
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2 votes
1 answer
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What clustering algorithms work best for datasets with only binary categorical features?

I have a dataset with a lot of binary categorical features and a single continuous target value. I would like to cluster them, but I am not quite sure what to use. In the past, I have used DBSCAN for ...
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1 vote
2 answers
51 views

Given a set of trajectories produced by a fixed policy, what is the the standard approach to estimate Q?

Let's say that I have a set of trajectories $\mathcal{D} = \{\tau_1, \dots, \tau_n\}$ produced by an agent acting in a (episodic) MDP with a fixed policy $\pi$. I would like to estimate the $Q$ ...
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1 vote
1 answer
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ML model to predict timeouts

I am new to ML and am trying to build a model to predict timeouts for a website. The website is being monitored once a minute and the data consists of a timestamp and the response time in seconds. E.g....
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Is there a multi-task RL algorithm that supports different action spaces for each agent?

I'm currently working on a project in which I need apply multi-task reinforcement learning. Over the same state space, each agent aims to do a separate task, but the action spaces of agents are ...
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1 answer
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Reinforcement learning algorithms for large problems that are not based on a neural network

I have a large control problem with multidimensional continuous inputs (13) and outputs (3). I tried several Reinforcement learning algorithms like Deep-Q-Networks (DQN), Proximal Policy Optimization (...
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1 answer
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Is there way to segment an image without labeling/classification, as well as supervised learning?

Is there way to segment an image without labeling/classification, as well as supervised learning? For an illustrative example, if one considers an image with a dog and a cup (we don't particularly ...
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51 views

Which algorithm can find the best combination of players to maximize the chance of getting a high score?

I am looking for the right terminology for this problem, so I know what to learn about. Imagine a population of 100 people in a town. The town has a sport team with 10 positions that play in ...
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Which ML algorithm/model should I use to learn temporal dependencies between binary variables?

Let's consider the following setting: We have 1000 binary variables (X1 ... X1000). At each time step each of the variable can either switch (1 to 0 or 0 to 1) or stay the same. I am looking for a ...
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11 views

How to approach in panel data using machine learning?

I have monthly electricity consumption data for the last year of 100k households. So there is a total (100k*12)= 1.2 million data points. I am willing to use this dataset to predict the individual's ...
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0 votes
1 answer
60 views

Avoid unintentional "merging" in cluttered object detection

I have a problem that has bothered me quite some time. With modern methods object detectors can often be accurately trained, even with small to medium sized datasets. However, there is one thing where ...
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0 answers
25 views

How to group multi-dimensional audio, video, and numerical data based on relatedness?

I have a data set that includes image arrays, point clouds, audio waveforms, and plain numerical data. I want to use unsupervised learning to group the data based on relatedness. So, if the audio and ...
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0 votes
1 answer
227 views

Compare Strings composed from 2-3 words using NLP/ML(Python)

I have a database of books. Each book have a list of categories that describe the genre/topics of the book (I use Python models). Most of the time, the categories in the list are composed from 1-3 ...
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0 votes
1 answer
55 views

Is there an approach where the output of one neural network is used to choose the next neural network?

I'd like to design a deep learning architecture in which the output of a primary neural network $M_{\theta}$ determines which neural network $N^i_{\alpha}$ in a set of secondary networks $\mathcal{N}$ ...
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Is it effective to use deep learning method to produce a 1D signal as output from a 2D image as input?

I have a 1D signal that will produce a 2D image after some image processing algorithm. Would it be possible and effective to use deep learning method to reproduce the 1D signal if I have the 2D image ...
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0 votes
1 answer
66 views

Are there any algorithms (even backtracking variations) that solve the sudoku in a way more similar to this approach?

I looked a bit online for Sudoku solvers and it seems like all the answers I found involve a backtracking algorithm. However, this is not how humans (at least not me) solve Sudoku. We don't place in ...
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Algorithms for solving Contextual Bandits Problem with multiples continuous actions

I am currently working on a problem that has 7 continuous actions and instantly gives a reward. I was thinking that there are Contextual-Bandits-Algorithms applicable to this kind of problem, but so ...
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0 votes
0 answers
41 views

What is the best machine learning algorithm for clustering dots based on coordinates $(x,y)$ with consideration of weight of the points?

I'm looking for a machine learning algorithm for clustering points based on their coordinates. Furthermore, I want to take into consideration the weights of each point. Suppose there is a weight in ...
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1 vote
1 answer
77 views

How to train an ML model to convert the given lyrics into a song by a particular singer?

I am interested in training a machine algorithm to convert the lyrics I give into a song by a particular singer. My language is non-English (south Indian) The songs are mostly monophonic (very few ...
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2 votes
0 answers
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What would be a reasonable option for clustering for unknown number of clusters and a lot of outliers?

I am implementing the CV detection pipeline with the use of SIFT and KNN Matcher. Image keypoints matched to the query keypoints produce the following image: The matched objects have a lot of key ...
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35 views

What is the best way to generate handwritten text documents?

I am new to generative models. I was wondering if it would be better to generate an image of a handwritten text document as a whole (which I don't know how exactly is done), or first generate ...
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2 votes
1 answer
94 views

How do I use machine learning to create an optimization algorithm?

Let's say that I want to create an optimization algorithm, which is supposed to find an optimum value for a given objective function. Creating an optimization algorithm to explore through the search ...
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3 votes
0 answers
65 views

Which algorithms are used to locate objects in a 3d space?

I can see mobile apps that can locate a 3D object on a surface with a mobile camera and you can turn around that object. What is the name of the algorithm(s) that is used for that purpose? Or, is ...
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2 votes
1 answer
91 views

Can AI be used for grading code copy exercises and adjust difficulty based on these scores?

I'm a senior in a bachelor Multimedia and Creative Technology. My experience is mostly full-stack web app development. For my bachelor's thesis, I need to do research in a subject I have no experience ...
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2 votes
0 answers
54 views

Which multi-agent reinforcement learning algorithm can I use when there are two types of agents with different action spaces?

Most of the papers on multi-agent RL (MARL) that I have encountered have multiple agents who have a common action space. In my work, my scenario involves $m$ numbers of a particular agent (say type A) ...
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2 votes
0 answers
38 views

What AI algorithm could I use to trap an agent in a game?

Imagine a game with grid size 10x10, there is a good guy and a bad guy and obstacles in the grid, i.e. essentially a maze. The goal of the bad guy is to find the good guy and trap him by erecting ...
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2 votes
0 answers
58 views

Non-face "deepfakes" in videos

Instead of changing faces (like James Bond to Putin) what if, given sufficient training data, I wanted to: Remove or add some windows from a brick house? Convert a glass of red wine to a glass of ...
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1 vote
1 answer
110 views

How can I use a ResNet as a function approximator for pixel based reinforcement learning?

I'd like to use a residual network to improve learning in image-based reinforcement learning, specifically on Atari Games. My main question is divided into 3 parts. Would it be wise to integrate a ...
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0 votes
0 answers
71 views

What algorithms minimize the log likelihood of sequential latent probabilistic models?

I am reading this paper, wherein they represent their model using a POMDP. Here is their latent probabilistic model that they have fit to the training data - Over here, $z_t \in Z$ represents the ...
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1 vote
0 answers
37 views

How to detect the sine wave signal with different frequency using neural networks?

I'm wondering if there is a way to use a neural network that can detect the noisy sine wave, where the frequency is not constant. In other words, I'm not looking for a solution that would detect the ...
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1 vote
1 answer
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What sort of out-of-the-box technology could be used to create work similar to artist Refik Anadol?

Refik Anadol has machines view actual pictures and then has the machine create its own images. This video shows some of the stuff he does. What kind of out-of-the-box tools (e.g. a Python package) or ...
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1 vote
1 answer
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What kind of algorithm or approach can I use to find a specific type of object in an image?

What kind of algorithm or approach can I use to find a specific type of object in an image? In particular, I am interested in finding an object like a windmill in an image taken, for example, from ...
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0 votes
0 answers
52 views

Evaluating species stagnation in NEAT

I'm exploring the NEAT algorithm, and among all of my questions on how to optimize my models, I was wondering how should I evaluate the stagnation of species in order to eventually extinct it. ...
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3 votes
1 answer
131 views

How to determine the quality of synthetic data?

I'm working on a VAE model to produce synthetic data of X-Ray diffraction spectrums. I try to figure out how I can measure the quality of the spectrums. The goal would be to produce synthetic data ...
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1 answer
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Compare the efficiency of a trained ML model with a non-learning-based method for solving the same problem

If a certain task T is solved by a non-learning-based method A (let's say, an optimization-based approach). We now train a machine learning model B (let's say a neural network) on the same task. What ...
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1 vote
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Are there any deep RL algorithms that work well on finite MDPs and non-trivial terminal rewards?

I notice that most Deep Reinforcement Learning (DRL) works focus on Markov Decision Process (MDP) with an infinite time horizon. Are there any algorithms that work well on finite MDP and non-trivial ...
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0 votes
1 answer
58 views

How to find "relationships" between two data representations?

I am a researcher in a field, and new to the whole of AI and machine learning techniques. May the following question is trivial or not framed in the ML language but I try my best. I have two sets of ...
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4 votes
2 answers
174 views

What algorithms are used in Artificial General Intelligence research?

I've read on wiki that already in 2017 there were over 40 institutions researching AGI, and I wonder what type of algorithms are being studied and developed in this field. For example, for comparison ...
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1 vote
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16 views

What is the best clustering method to detect anomalies for data with mostly categorical data?

I have a dataset with about 85 columns. Out of the 85 columns, 70+ are categorical. My goal is to identify the outliers in this dataset through clustering methods as I do not have a target column. ...
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0 votes
1 answer
50 views

Fitting a Gaussian distribution into another distribution

Assume we have two vectors, containing random samples (maybe audio data?). Their distribution can be approximated to a normal distribution, so we can calculate their mean and standard deviation. I am ...
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2 votes
0 answers
36 views

Is there a technique for analyzing the relationship between time-series clusters?

I have two time-series datasets (temperature and speed of the vehicle). I will use Agglomerative Hierarchical Clustering and DTW to cluster both datasets. I am looking for a technique (like regression ...
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1 vote
1 answer
45 views

Machine Learning in relation to personality and behaviors predictions

I am tasked with making a machine learning model that predicts personality traits and behaviours of children based on simple and interactive quizzes. Currently I am lost and have no idea where to ...
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  • 151
1 vote
1 answer
52 views

What kind of neural network should I build to classify each instance of a time series sequence?

Let's say I have the time-series dataset below-left. I would like to train a model in such a way that, if I feed the model with an input like the test sequence below, it should be able to classify ...
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  • 133
0 votes
0 answers
74 views

What are the state-of-the-art learning algorithms for contextual bandits with stochastic rewards

I am building a solution for an environment with stochastic rewards in an online setting. I am wondering what the state of the art is in this setting. Is it $\epsilon$-greedy (with logistic regression)...
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