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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6 views

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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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
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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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20 views

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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20 views

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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17 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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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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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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25 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
33 views

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

Calculus is a branch of mathematics that 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, higher-order ...
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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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1answer
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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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25 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 usefulness of gradients in some domains of artificial intelligence, especially in optimization. First order gradient: ...
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1answer
37 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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40 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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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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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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Is there any existing mechanism that allows us to pass input from randomly selected layers of neural network per iteration?

Consider the following neural network with $\ell$ layers. $$i_0 \rightarrow h_1 \rightarrow h_2 \rightarrow h_3 \cdots \rightarrow h_{\ell-1} \rightarrow o_{\ell} ,$$ where $i, h, o$ stands for ...
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1answer
28 views

Are there any stats available on the usage of libraries by deep learning researchers?

I know three Python libraries that are popular in deep learning research community: Keras, PyTorch, Tensorflow. I don't know much about Theano. This question is not about the efficiency, flexibility ...
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39 views

How much research, approximately, is done in ANNs?

Does someone know where can I find information about how much research, nowadays, is done in ANNs? I've checked in this document Redes Neuronales: Conceptos básicos y aplicaciones, Universidad ...
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Is there a gentle introduction to reinforcement learning applied to MDPs with continuous state spaces?

I am looking for a gentle introduction (videos, lecture notes, tutorials, books) on reinforcement learning (MDPs) involving continuous states (or very large cardinality of state space). In particular, ...
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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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1answer
30 views

Where can I find the original conference paper that introduced Q-learning and Deep Q-Learning?

I tried searching a lot, but I could neither find the paper that introduced Q-Learning nor the paper that introduced Deep Q Learning. If anyone knows anything about it please do tell me.
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What is the sample complexity of Monte Carlo Exploring Starts in RL?

We can use a model-free Monte Carlo approach to solving an MDP $(S,A,R,P,\gamma)$ with transition dynamics $P$ unknown by estimating Q-values by rolling out trajectories starting from random states $...
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20 views

How many MAC operations are executed in one inference/training cycle of Google BERT?

I wonder if there is any information about the amount of MACs are executed for one training/inference cycle of Google BERT. I only found information about the number of layers and parameters here. ...
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1answer
53 views

How could Bayesian neural networks be used for transfer learning?

In transfer learning, we use big data from similar tasks to learn the parameters of a neural network, and then fine-tune the neural network on our own task that has little data available for it. Here, ...
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Object localisation and window size(can’t use learning methods). Share the resources to solve this problem

Given two images($I_1$, $I_2$) and both images contain a similar object. First, find the location of the windows which contains the object for each image. For example, let $I_{n \times n}$ is a 2-D ...
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61 views

Is there a recent book that covers the theoretical and philosophical aspects of artificial intelligence?

What are some recent books that introduce AI and neural networks while also discussing the related philosophical issues, like epistemology and whether AI is really thinking, etc.?
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Is there any work that applies the approach in "Finite-Sample Convergence Rates for Q-Learning and Indirect Algorithms" to standard Q-learning?

I am trying to mathematically characterize the finite sample convergence rates for Q-learning. To this end, I have read the following papers Learning rates for Q-learning, by Eyal Even-Dar et al.; ...
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22 views

What is "fill" algorithm used for image resizing and cropping?

I was going through this documentation directed by Codelab-Developer-Google. In order to resize an image, the notebook is using the "fill" algorithm. See the below code ...
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1answer
43 views

What is the state of the art in melody generation?

Generative Adversarial Networks can generate realistic photos of people, such as thispersondoesnotexist.com. I wonder whether one can train an artificial intelligence on a batch of plain solo melodies ...
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23 views

What is the best way to train neural network with imbalanced mixed data (images and structured data)?

I have structured data and image data to solve a regression problem. One sample of structured data can be related to N images. If I use only structured data, I get decent performance, but not enough ...
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10 views

Increased performance using monotonic constraints with neural networks

I see that with the xgboost library, we can tell the training process that some features are necessarily monotonic with the model's output - https://xgboost.readthedocs.io/en/latest/tutorials/...
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19 views

Are there any good references that describe the equations of the forward pass of Graph Neural Networks?

I am trying to program Graph Neural Network from scratch. Can the community please suggest a good reference/s to read about the equations of the forward pass in Graph Neural Networks, especially in ...
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1answer
47 views

Which AI techniques are there that combine multiple models to make sense of data at different stages?

I have been working to design a system that uses multiple machine learning models to make sense of data that is dynamically webscraped. Each AI would handle a specific task, for example: An AI model ...
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19 views

What are the most relevant resources that define the face detection problem formally?

I am new to AI, and I am a bit lost about finding the relevant materials that define the face detection problem formally/mathematically. Can anyone help me formally define face detection, or at least ...
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26 views

Positional encoding in convolutional layers

Positional encoding (PE) is an essential part of the self-attention layers in the transformer architectures since without adding it in some way (fixed of learnable) to the input embeddings model has ...
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1answer
40 views

Why did Distributional Q Learning go out of popularity?

I read some papers (for example, this) and blogs that spoke about the advantages of distributional Q learning. However, it no longer seems to come up in literature. Did it have any shortcomings that ...
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1answer
53 views

Can Reinforcement Learning be used to generate sequences?

Can we use reinforcement learning for sequence-to-sequence tasks? If yes, whether or not this is a good choice, how could this be done?
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9 views

How can I design a machine translation model that produces a mapping between the words in the source and target sentences?

I have a dataset of sentences of language X and Y X Y abc def lang xyz pqrt mno uages I want to have an output as a table with word-by-word translation (...
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2answers
81 views

Book(s) for text embedding

Text here refers to either character or word or sentence. Is there any recent textbook that encompasses from classical methods to the modern techniques for embedding texts? If a single textbook is ...
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18 views

Current extensions of the "Turing Test"?

In 2014 it was widely reported that the Turing Test had been passed, and that this was a major AI milestone. See: Computer AI passes Turing test in 'world first [BBC]; Turing Test Success Marks ...
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23 views

Which well known node embedding algorithms to use for weighted graphs?

I am looking for a node representation learning algorithm to generate node embeddings that supports weighted graphs. I modified GCN to support weighted graphs, but I want to know an algorithm that ...
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13 views

How to Approach a Conversation Detector?

I am currently looking for a way to detect if a conversation is occurring. The meaning of the conversation is not important for this case. One approach that seems viable is to try to detect a voice ...
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2answers
77 views

Why was the VC dimension not defined for all configurations of $d$ points?

Let's start with a typical definition of the VC dimension (as described in this book) Definition $3.10$ (VC-dimension) The $V C$ -dimension of a hypothesis set $\mathcal{H}$ is the size of the ...
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212 views

What are the typical sizes of practical/commercial artificial neural networks?

I'm interested in artificial neural networks (ANN) and I wonder how big ANNs in practical use are, for example, Tesla Autopilot, Google Translate, and others. The only thing I found about Tesla is ...
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27 views

Is there literature on Neural Network with activation functions of bounded domain?

I think to have found a somewhat interesting connection between neural networks and another area of mathematics. However, it requires the activation functions in the network to have a bounded - ...
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21 views

Is it possible to do object detection on an object classification dataset?

I'm new to computer vision, which I find fascinating. I wonder whether it is possible or if there has been any research into going from object recognition data to object detection. In other words, ...
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Is there a different approach, other than MAML combined with LSTM, for meta-regression of time-series data?

I am working on the calibration of low-cost air sensor data (a time series regression problem). My primary focus is to use some meta/ few-shot learning approach to solve this problem with fewer data. ...

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