Questions tagged [reference-request]

Use when requesting examples of research or research papers, books, articles, blog posts or courses. For example, "Is there any published research about X?" or "What are good examples of Y in research?".

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Is there some neural network that implements Least Squares?

I would like to build supervised NN that gets a matrix $A$ and vector $b$ as inputs and returns $x$ as a close result of the Least Squares algorithm for $Ax=b$. I looked for so works in the field and ...
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18 views

Is it possible to train an AI to organize frames in chronological order?

I would like to know if there is a neural network or some other kind of AI that would be able to reconstitute randomly shuffled frames into a video or slideshow that makes chronological sense? The ...
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Tokenization for treelike structures

I'm pretraining a BERT (bigbird) model to use with SMILES encoding of chemicals. This kind of data is a treelike structure in the form of a string with a single bracket type. Usually this tree isn't ...
1 vote
1 answer
38 views

Could one still learn a good policy by doing a backprop every fixed number of steps within an episode?

Waiting an entire episode before doing a backprop can build up a very large computational graph, which is a burden on memory. Could one still learn a good policy by doing a backprop every fixed number ...
1 vote
0 answers
26 views

What is the depth reached by chess-AI agents on a regular computer?

I'm looking for some reference for the number of lookahead steps typically used by chess agents (Stockfish / Leela Chess Zero / others?) From a quick search, I found that the answer depends on: ...
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9 votes
2 answers
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How can I encode angle data to train neural networks?

I am training a neural network where the target data is a vector of angles in radians (between $0$ and $2\pi$). I am looking for study material on how to encode this data. Can you supply me with a ...
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17 views

The episode length increases at the start till it reaches a peak then decreases. What can cause this unexpected behavior?

I am running the A3C algorithm to evaluate a policy based on a policy gradient method. I observe an unexpected behavior at the start of the episode in the reward and episode length. As shown in the ...
0 votes
1 answer
82 views

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 ...
2 votes
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27 views

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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How to integrate program synthesis into program maintenance and evolution (if it is possible at all) - possible reference request?

Program synthesis is one of the most active research fields today, e.g. works by Microsoft Research https://arxiv.org/abs/2208.05950 and SalesForce Research https://arxiv.org/abs/2203.13474. I ...
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1 vote
1 answer
128 views

Are there free and open-source audio versions of Generative AI programs like Stable Diffusion?

Generative AI is being used to create amazing art; first through paid services like Midjourney and now also with free, open source alternatives like Stable Diffusion. Now you can even generate art in ...
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Label based normalizing flow

I am interested in capturing higher-dimensional embeddings of a image dataset as a gaussian noise, such that a specific region of gaussian noise corresponds to embedding of a particular label. How do ...
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1 vote
1 answer
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machine learning for a budgeting application

I am interested in finding references and previous applications where prior year budgets are analyzed to provide guidance for a current year budget. Specifically, each year some two thousand items ...
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1 vote
2 answers
49 views

References on Theoretical Bandit Problem

I am going to start learning the bandit problem and algorithm, especially how to bound the regret. I found the book ``Bandit Algorithms'' but it is not easy to follow. It is based on advanced ...
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1 answer
135 views

How can we approximate infinite horizon MDP with finite horizon MDP in the context of reinforcement learning?

For a given value of "discount factor" (and reward values' range) in fixed finite horizon markov decision process (MDP), upto how many episodes we have to extend this MDP so that we can ...
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8 views

References for Stochastic Process for Sequential Decision Making

I am reading papers on Multi-armed bandit problem. In these papers, they use some notations in measure-theory like filtration, adapted filtration, and so on. Also, to prove theorems, many papers ...
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1 answer
107 views

Papers on Prompt Engineering

I am into AI in general and NLP in particular. Besides, I have a background in philosophy, and the new LLMs like GPT-3 seem to have exciting capabilities. I want to study prompt engineering (for ...
1 vote
2 answers
58 views

Can I minimize a mysterious function by running a gradient descent on her neural net approximations?

So I have this function let call her $F:[0,1]^n \rightarrow \mathbb{R}$ and say $10 \le n \le 100$. I want to find some $x_0 \in [0,1]^n$ such that $F(x_0)$ is as small as possible. I don't think ...
0 votes
1 answer
22 views

Is there any work done on topic agnostic binary topic classification?

In the recent preprint paper Tree-based Focused Web Crawling with Reinforcement Learning a new model is introduced to classify web pages called KwBiLSTM. The input to this model is a featurized ...
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7 votes
2 answers
995 views

Deep Learning with Best-so-far instead of Where-you-are

It is my understanding that when training a Deep NN in Tensorflow/PyTorch/... we only keep the current state of the network in memory, except perhaps when we manually decide to save the current ...
2 votes
0 answers
113 views

Is there a literature on the time complexity of Neural Networks?

There exist various blog posts describing the time complexity of Fully Connected Neural Networks (1, 2, 3, 4); Convolutional Neural Networks (CNN) (5) and of Long Short-Term Memory (LSTM) networks (6)....
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4 votes
2 answers
50 views

Is there any proper literature on the types of features that different layers of a deep neural network learn?

Let's consider a deep convolutional network. It seems that there is some consensus on the following notions: 1. Shallow layers tend to recognise more low-level features such as edges and curves. 2. ...
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3 votes
1 answer
349 views

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 ...
1 vote
1 answer
265 views

Does LSTM provide any unique value or advantages compared to other algorithms, including "vanilla" RNN?

I have heard a lot of hype around LSTM for all kinds of time-series based applications including NLP. Despite this, I haven't seen many (if any) applications of LSTM where LSTM performs uniquely well ...
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0 answers
9 views

Help finding a recent paper describing how current DL methods are not inspired by biology

I know this is a very long shot, but about a month ago I came across a paper describing how current DL architectures are not inspired by biology, and how the fact that most research only aims to push ...
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2 votes
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72 views

Today's Practicality of Bayesian Neural Networks

Just having heard lately about BNNs (wow, ANNs and CNNs are clear; now there's a B? What's that? Ahh, Bayesian ;-)) and quickly getting their main idea and focus, that is, weights not being pure ...
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Deriving the cross entropy loss via maximum-likelihood estimation?

For multi-class classification problems, we use the cross entropy loss, which can be derived from a multinomial distribution via the maximum likelihoos estimation method. I've already tried to derive ...
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0 votes
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50 views

Is Bayesian Reinforcement Learning used as off-policy RL?

Are there any examples where Bayesian Reinforcement Learning is used as off-policy RL? What are the pros and cons of using it for this purpose?
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17 views

How do we call a transformer having N encoders and M decoders and a learnable cross-connectivity between encoders and decoders?

How do we call a transformer having N encoders and M decoders and a learnable cross-connectivity between encoders and decoders? I am interested particularly in the case when M=1, but I imagine that it ...
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1 vote
1 answer
147 views

Current state of the art and datasets for combining NLP and CV?

I was considering a scenario where natural language processing (NLP) and computer vision (CV) are combined, for example in extended reality systems that get as input both natural language and non-...
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0 votes
0 answers
20 views

Can machine learning algorithms automatically create formulations of optimizing algorithms?

Suppose we want to create an optimization algorithm which should be able to find an optimum value for non-convex optimization problems. Usually meta-heuristics are used for this purpose. Designing a ...
2 votes
1 answer
50 views

Does pairing children with their parents cause any harm (in a genetic program)?

If you pair parents with their children (with a cross-over) does this prevent making individuals which are more fit or does this cause other side effects which are harmful to the genetic process? I ...
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3 votes
1 answer
108 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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1 vote
2 answers
188 views

Why does triplet loss allow to learn a ranking whereas contrastive loss only allows to learn similarity?

I am looking at this lecture, which states (link to exact time): What the triplet loss allows us in contrast to the contrastive loss is that we can learn a ranking. So it's not only about similarity, ...
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0 votes
0 answers
52 views

What are some solid metrics to evaluate/compare the outputs of explainable algorithms?

Consider a learned CNN image classifier and a task that focuses on studying the outputs of explainable algorithms, such as integrated gradients and grad-cam, on the classifier's predictions. I am ...
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0 votes
1 answer
150 views

Are there any guidelines on how to map the state space to integers in the case tabular RL algorithms?

Let's say that you want to solve a problem with a tabular reinforcement learning algorithm, for example, Q-learning. You can represent the value function $Q(s, a)$ as a $|\mathcal{S}|\times |\mathcal{...
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1 vote
0 answers
30 views

Is there any research on anger and distrust detection (presence and level of political cynicism)?

The undergrad research project I'm working on would require me to detect presence and level of political cynicism from reddit posts. According to definition political cynicism consists of anger ...
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0 votes
0 answers
58 views

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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2 votes
1 answer
102 views

How to construct a reward function for a "wait and see" problem

I'm working on a problem that I think could probably be represented as a reinforcement learning task, but I'm uncertain about how to design the reward function. The core task is essentially a ...
0 votes
1 answer
62 views

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 ...
3 votes
2 answers
178 views

How to model a multi-agent reinforcement learning problem where actions of different agents can take different durations?

I am confused on a conceptual scale how I would be able to model a multi-agent reinforcement learning problem when each agent performing an action would take different durations to complete the action....
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0 votes
1 answer
29 views

How can I vectorize fictional single word (not sentence!) for classification?

I am working on fictional single words (names) generator that have to sound like words from a given sample. I have the generator up and running that gives reasonable words 70% of time. I thought of ...
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5 votes
1 answer
128 views

Does the term "data augmentation" imply increasing the training dataset?

I have a manuscript that has been reviewed and one of the reviewers commented on my use of the term " data augmentation", saying that it might not be the appropriate term in my case (...
0 votes
1 answer
46 views

What would be a good cost function based on both saliency-maps and labels?

I have a number of input samples where: every input sample has both a label and a reference-map. This reference-map gives a score to each location of an input sample. The score defines how much this ...
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3 votes
1 answer
483 views

Is it possible to train an AI to bring a picture story in the correct order (correct story flow)?

I want to know if it is possible to train a neural network (or some other kind of an AI) to bring a simple picture story in the correct order, if it is in random order, so that the story has the ...
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0 votes
0 answers
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Unsupervised methodologies to detect collective anomalies in transaction data

I am researching various methodologies to detect collective anomalies in transactions data. I have seen some supervised approaches, but not the unsupervised ones. Please share any resources or ...
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0 votes
0 answers
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Which NLP methods use gradient and activation methods?

I am doing a literature review of gradient-based methods for NLP. Yet, apart from linear and logistic regression, I have little knowledge of other methods using the gradient. So, I have no knowledge ...
0 votes
0 answers
13 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 ...
0 votes
0 answers
20 views

Given the high resolution signal and the low pass filter (kaiser filter), is there a way to reconstruct the low resolution signal?

When we upsampling a discrete 1d signal by 2x, we first interleave the signal by 0, then pass through a low pass filter. low resolution signal [x1, x2, x3, x4] -> interleave 0 -> [x1, 0, x2, 0, ...
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2 votes
1 answer
77 views

How might AI analyze abusive discussion using natural language grammar?

Opening thoughts This does not only apply to SE comments, but the idea in general. This is not a Question for Linguistics.SE; those Questions might come later, after AI analysis. Example Linguistics ...
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