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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Algorithms for average reward reinforcement learning in continuous/general state-action space
I see that discounted reward reinforcement learning has been extensively studied in the literature. However, the average reward metric receives less attention, and it looks like algorithms for this ...
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Match two paragraphs of text
I'm building a friend finder app and I need to match people based on a paragraph of text. Here is an example of what I mean:
Person A:
I love walking and going to the beach, I also love reading and ...
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What are the most effective methods and tools for summarizing long-form content like articles, editorials, and discussion threads for an app?
With users expecting instantaneous information and no compromise on in-depth details, app developers are challenged to condense long-form content such as articles, editorials, and discussion threads ...
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Is there a most general-purpose unsupervised learning algorithm?
I was thinking about training a model on non-linguistic material like video, and I was wondering if it could form concepts about the world, and also somehow form composite concepts or conceptual ...
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How to tokenize compound sentences based on the conjunctions?
I am trying to tokenize sentences of a document for aspect-based sentiment analysis. There are some sentences that consist of more than one topic. For example,
The touch screen is good but the ...
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Is there any interpretation method suitable for CNNs which do regression tasks?
I mainly tackle regression problems by CNNs, and want to find a reliable method to calculate the heatmaps for NN's results. However, I find almost all interpretation methods including CAM is used for ...
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What models/algorithms besides variational autoencoders can I use to transform a discrete input into a differentiable latent space?
Let's say I have a discrete input and want to transform it into a differentiable latent space. What models/algorithms besides variational autoencoders can I use?
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What strategies are there to reduce the variance of the policy gradient estimator of the REINFORCE algorithm?
What strategies are there to reduce the variance of the policy gradient estimator of the REINFORCE algorithm?
I know one possibility is to subtract a baseline as a running average of rewards from past ...
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Machine Learning Methods commonly used when data are scarse
It is well-known that deep neural networks require lots of data to perform reliably and well. A commonly-cited statistic is that you need at least 10,000 examples per class for a classification ...
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What are some non-RL-based approaches to solving a typical bin assignment problem?
What are some non-RL-based approaches to solving a typical bin assignment problem, i.e., given a set of items (can be multidimensional), find the bin/knapsack/target which best packs (with minimum ...
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Are there Reinforcement Learning algorithms specialized for the case $\gamma=0$?
I have a Reinforcement Learning problem where the optimal policy does not depend on the next state (ie gamma equals 0). I think this means that I only need an efficient exploration algorithm coupled ...
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Image classifier model which predicts objects and it's relevant areas with a combination of words
I have experience with image classification models such as CNN and Vision Transformers but this time I want to try a new thing (For me).
First please check the below image to understand what I want
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What is the best approach/model for classifying document images with over 70+ classes of documents?
What is the best approach/model for classifying document images with over 70+ classes of documents? I have tried LayoutLM which is a model that incorporated both NLP and Computer vision to classify ...
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How is it possible to detect anomalies in batches of 2 minutes of web access logs?
I have data coming from web access logs in the following form:
...
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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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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What sort of out-of-the-box technology could be used to create work similar to artist Refik Anadol? [closed]
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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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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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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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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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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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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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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