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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56 views

Are there any works that deal with 2D pose estimation in videos?

Since pose estimation is often a task where spatial-temporal context should be helpful in finding subsequent key points, I thought there should be many papers on it. However, I could not find any work ...
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1answer
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What are the base rules for the symbolic integration implementation?

I want to implement a full symbolic integration. To achieve this. I've learned from Prof. Patrick Winston's AI lecture that Matlab uses 12 safe transformations, like that constant out, sums, etc. 12 ...
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Is there a paper/article on contextual $\epsilon$-greedy algorithm?

I am reading the paper A Contextual-Bandit Approach to Personalized News Article Recommendation, where it refers to $\epsilon$-greedy (disjoint) algorithm. I suspect, that it is just a version of a K-...
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1answer
75 views

What are knowledge graph embeddings?

What are knowledge graph embeddings? How are they useful? Are there any extensive reviews on the subject to know all the details? Note that I am asking this question just to give a quick overview of ...
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25 views

How do we give recommendations when users create/post content (like in YouTube)?

I've explored tools like amazon personalize, etc. for generating recommendations. It seems like amazon personalize is appropriate when all the content is with the company/a single entity. For example, ...
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16 views

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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1answer
52 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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10 views

How does the distribution of the parameters change in logistic regression?

I have my own data to train a logistic regression model (for a multi-class classification task), and I want to know how the distribution of weight parameters changes after each update with gradient ...
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1answer
72 views

Which historically relevant programs were developed in LISP in the early days of AI?

LISP stands for List Processing. In this functional programming language, programs look like lists and can be treated as data (hence the name). It was designed by John McCarthy (one of the official ...
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1answer
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Is there a mathematical formalism to deal with a missing reward signal?

Typically, a Reinforcement Learning learning problem is formalized as finding an optimal policy for a Markov Decision Process (MDP). In many real-life situations, however, an agent can only get ...
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Is there a way to adapt Particle Swarm Optimization to an incremental/online learning setting?

As stated in the title, is there a way to adapt PSO to an online scenario where new data samples arrive continuously? In more detail: suppose that I have a classifier with several parameters for which ...
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1answer
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Which introductory courses (preferably video lectures) could I use to learn ML for applying ML to black hole simulations? [closed]

I am a Ph.D. candidate in High Energy Physics and my research involves numerical simulations and data analysis. I am interested to learn Artificial Intelligence and Machine Learning from the basics so ...
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Are there any resources that introduce the basics of online machine learning?

Are there any resources (either books, articles, or tutorials) that introduce the basics of online machine learning? For example, this website has nice lecture notes (from lec16) on some of the ...
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How should I read a deep learning paper?

I have a background in mathematics and I am accustomed to reading papers with lemma and proofs. When I see a deep learning paper, they seem to be of practical nature. How can I improve my reading and ...
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Would AlphaZero work just with a value network?

There is a nice post about the intuition why AlphaZero works. One of the advantages of using a policy network in the games where a perfect simulator is available (such as chess) is to save computation ...
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Is there any other (possibly less popular) approach to create AI apart from statistical methods?

From what I have gathered so far, an AI has some prior (stored in the form of some probability distribution), and, based on experiences/data, changes the distribution (via Bayes rule) accordingly. ...
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Reference needed for neural networks finding solutions of PDE's

DL-PDE prescribes a way to feed a neural network data, which in turn comes up with a PDE of the form $$u_{t}(t,x,y) = F(x,y,u,u_{x},u_{y},u_{xx},u_{xy},u_{yy},...) \hspace{0.5cm} (x,y) \in \Omega \...
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2D models on 3D tasks (convolutions): simple replace?

2D tasks enjoy a vast backing of successful models that can be reused. For convolutions, can one simply replace 2D operations with 3D counterparts and inherit their benefits? Any 'extra steps' to ...
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Does there exist functions for which the necessary number of nodes in a shallow neural network tends to infinity as approximation error tends to 0?

The Universal Approximation Theorem states (roughly) that any continuous function can be approximated to within an arbitrary precision $\varepsilon>0$ by a feedforward neural network with one ...
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1answer
56 views

Is there any paper that shows that multi-channel neural networks are universal approximators?

Lately, I have been reading a lot about the universal approximation theorem. I was surprised to find only theorems about "single-channel" standard networks (multi-layer perceptrons), where ...
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Apart from ontologies, which other methods for knowledge representation are there in Artificial Intelligence?

From what I have been reading, I see statements like Ontology is a common method used for knowledge representation in artificial intelligence. But there is never really a discussion around what ...
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1answer
57 views

CNN Architectures for local features vs global context

Kaparthy in his blog post said [this] hints at the kinds of architectures we’ll eventually explore. As an example - are very local features enough or do we need global context? I'd like to gain ...
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1answer
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Is there a tutorial for understanding the proof of convergence for TD learning?

I'm reading the article An Analysis of Temporal-Difference Learning with Function Approximation (1997), but the mathematics inside seems overly complicated for me. Answers to some similar questions ...
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1answer
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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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How does $\alpha$ affect the convergence of the TD algorithm?

In Temporal-Difference Learning, we update our value function by $V\left(S_{t}\right) \leftarrow V\left(S_{t}\right)+\alpha\left(R_{t+1}+\gamma V\left(S_{t+1}\right)-V\left(S_{t}\right)\right)$ If we ...
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Why does TD (0) converge to the MLE solution of the Markov model?

Why does TD (0) converge to the MLE solution of the Markov model? Let's take the Example 6.4 in Sutton and Barto's book as an example. Example 6.4: You are the Predictor Place yourself now in the ...
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1answer
41 views

Is there a benchmark for multi-objective evolutionary algorithms?

I'm working on a project for an evolutionary algorithms course, and the problem we're trying to solve is multi-objective. We'll use NSGA-II but we also wanted to compare with some other MOEAs, however,...
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References for the convergence of gradient-based algorithms for training neural networks

I'm looking for some good references that give convergence results of training neural networks. I'm decently familiar with works that analyze the convergence of SGD, and, in particular, I really like ...
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29 views

Connection between multi-label classification and multi-class classification

For a dataset with multi-label judgment, e.g., coco dataset but where we only want to predict the most possible label. There're multiple ways: train as multi-label learning and predict as a multi-...
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1answer
47 views

What is the name of the method for the smart extend of image surroundings?

I'm looking for the name of the method (or algorithms family, or research body) used for the smart extend of image surroundings. For example, the method I'm looking for would take this image: And ...
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34 views

Did the unsolved XOR problem in "Perceptrons: An Introduction to Computational Geometry" 1969 book really cause the winter of the AI in 1974?

Winter of AI definition: periods of reduced funding and interest in artificial intelligence research, due to unmet expectations after a period of hype. There have been at least two major AI winters ...
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Why does conditioning neural network function on adjacency matrix of graph allow for distribution of gradient information from the supervised loss?

I was reading the following paper here and had a question about the paragraph on page 1 (in the introduction). The equation being referred to is: $$ \mathcal{L} = \mathcal{L}_0 + \lambda \mathcal{L}_{\...
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searching for finding some mental disorder simulation by AI models

I have tried to find some AI models which could create one sense of the autism simulated video on the below questions: Searching for finding the similarity of the Autism verbal brain functionality ...
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How should I choose a reinforcement learning algorithm? [closed]

I'm starting a new RL project. I'm familiar with Deep Q-Learning because of an old project where I used it, but I'm not sure I chose correctly back then. Why should or shouldn't I choose DQN, or any ...
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22 views

Book/course recommendation on game theory application to multi-agent system (reinforcement learning)

Is there any great game theory book or course that discusses the application of game theory to modern reinforcement learning or multi-agent systems? Or a classic reference book that can help me get a ...
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18 views

proof of convergence for the random forest algorithm

I am looking for the proof of convergence of the random forest algorithm. A cursory google search shows many, but I do not understand which version (original?) of the algorithm this is. Can you kindly ...
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31 views

Is Speech to Speech with changing the voice to a given other voice possible?

Background: I am working on a research project to use (demonstrate) the possibilities of Machine Learning and AI in artistic projects. One thing we are exploring is demonstrating deep fakes on stage. ...
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1answer
43 views

Where can I read about upsampling methods in detail?

In deep learning, we encounter the upsample blocks several times, especially when we deal with images. Consider the following statements from description regarding UPSAMPLE in PyTorch The algorithms ...
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34 views

Cost functions for reducing Tensors to 1-dimensional arrays?

I'm interested in the IT side, here, specifically how I most efficiently store a tensor in a one dimensional data structure. My assumption is that certain approaches will be more expensive than others,...
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Simple example for average log-probability

Consider the following statements from Chapter 5: Machine Learning Basics from the book titled Deep Learning (by Aaron Courville et al.) For tasks such as classification, classification with missing ...
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1answer
65 views

What are the Calculus books recommended for beginner to advanced researchers in artificial intelligence?

Calculus is a branch of mathematics that primarily deals with the rate of change of outputs of a function w.r.t the inputs. It contains several concepts including limits, first-order derivatives, ...
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Is there a survey that describes the most effective approaches for an answer retrieval problem?

I have a dataset that contains pairs of a question and an answer. My problem is to train a model that can search for the right answer from the pool of my answers given the newly input question, so ...
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36 views

Has the idea of using different learning rates for different layers been explored in the literature?

I wonder whether there are heuristic rules for the optimal selection of learning rates for different layers. I expect that there is no general recipe, but probably there are some choices that may be ...
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1answer
99 views

Is there any way to train a neural network without using gradients?

The only algorithm I know for updation of weights of a neural network is based on gradients. The update equation can be roughly written as $$w \leftarrow w - \nabla_{w}L$$ where $\nabla_{w}L$ is the ...
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30 views

Is there any significance for higher order gradients in artificial intelligence?

Although I don't know in detail, I am aware of the following facts regarding the use of gradients in some domains of artificial intelligence, especially in optimization. First order gradient: It ...
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35 views

Couldn't the self-attention mechanism be replaced with a global depth-wise convolution?

The main advantages of the self-attention mechanism are: Ability to capture long-range dependencies Ease to parallelize on GPU or TPU However, I wonder why the same goals cannot be achieved by ...
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1answer
44 views

Looking for a textbook on Bayesian Inference

I am looking for a textbook that is a nice entry level to Bayesian Inference. I was hoping that there is a nice blend of theory and applications (data sets) on how concepts are applied. Programming ...
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41 views

Can reinforcement learning be used to learn an unknown analytical function (for example, $y = x^2$ )?

Are there any examples for RL to learn analytical functions (for example, $y=x^2$)? What are the considerations when constructing the environment? Are there any literature that analyzes the difficulty/...
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14 views

Is it possible to train a model on files of code and output questions about it?

I want to know if it is feasible to use deep learning to generate homework questions for a course on logic. My input data of programming functions and desired output of respective homework questions ...
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2answers
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Does regularization just mean using an augmented loss function?

We need to use a loss function for training the neural networks. In general, the loss function depends only on the desired output $y$ and actual output $\hat{y}$ and is represented as $L(y, \hat{y})$. ...

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