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Are both the training and inference systems required in the same application?

From what I understand, there are 2 stages for deep learning: the first is training and the second is inference. The first is often done on GPUs because of their massive parallelism capabilities, among other things. The second, inference, while it…
Mahmoud Abdel-Mon'em
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Is it possible to classify data using a genetic algorithm?

Is it possible to classify data using a genetic algorithm? For example, would it be possible to sort this database? Any example in Matlab?
Ricardo Pouças
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How do I use a taxonomy and the support vector machine for question classification?

I am going to develop an open-domain natural language question-answering (NLQA) system, and will use the support vector machine (SVM) as the machine learning (ML) model for question classification. The data that I have is from a cube, containing…
lilienfa
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How to handle cycles in minimax algorithm

For example, I am implementing AI for turn based game and have enough computational resources for build full game tree. My problem is the game can be infinite if both players will repeat moves and my minimax implementation stucks because game tree…
Terri Erickson
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In logistic regression, why is the binary cross-entropy loss function convex?

I am studying logistic regression for binary classification. The loss function used is cross-entropy. For a given input $x$, if our model outputs $\hat{y}$ instead of $y$, the loss is given by $$\text{L}_{\text{CE}}(y,\hat{y}) = -[y \log \hat{y} +…
hanugm
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In the field of Deep Learning research, what considerations do researchers take into account when inventing new neural network models?

I am not a researcher, but I am curious to know what considerations are relevant to take into account during research for the invention of a new neural network model, and what relevant knowledge researchers typically possess in the area. And an…
Andres Sarmiento
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Is an embedding a representation of a word or its meaning?

What does the term "embedding" actually mean? An embedding is a vector, but is that vector a representation of a word or its meaning? Literature loosely uses the word for both purposes. Which one is actually correct? Or is there anything like: A…
hanugm
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What makes a transformer a transformer?

Transformers are modified heavily in recent research. But what exactly makes a transformer a transformer? What is the core part of a transformer? Is it the self-attention, the parallelism, or something else?
AB Saravanan
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What does Brooks mean by "representation"?

For a class, I'm reading Brooks' "Intelligence without representation". The introduction is dedicated to slating representation as a focus for AI development. I've read that representation is the problem of representing information symbolically, in…
Jansky
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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 this one: "A full build of Autopilot neural…
Mitarano
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Why can't cognitive architectures achieve general intelligence?

Newbie here. I recently read about cognitive architectures (see: https://en.wikipedia.org/wiki/Cognitive_architecture). They are supposed to be modeled after the human mind and represent a promising approach towards artificial general intelligence…
Anonymous
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Are neurons instantly feed forward when input arrives?

Let's say I have a neural network with 5 layers, including the input and output layer. Each layer has 5 nodes. Assume the layers are fully connected, but the 3rd node in the 2nd layer is connected to the 5th node in the 4th layer. All these numbers…
Miemels
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What are the major differences between multi-armed bandits and the other well-known algorithms (DQN, A3C, PPO, etc)?

I have studied in the past different algorithms, i.e. DQN, DDQN, REINFORCE, A3C, PPO, TRPO, so on. I am doing an internship this summer where I have to use a multi-armed bandit (MAB). I am a bit confused between MAB and the other above…
notaprogrammertoday
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Why object detection algorithms are poor in optical character recognition?

OCR is still a very hard problem. We don't have universal powerful solutions. We use the CTC loss function An Intuitive Explanation of Connectionist Temporal Classification | Towards Data Science Sequence Modeling With CTC | Distill which is very…
user40943
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What does "statistical efficiency" mean in this context?

Consider the following statement(s) from Deep Learning book (p. 333, chapter 9: Convolutional Networks) by Ian Goodfellow et al. Convolution is thus dramatically more efficient than dense matrix multiplication in terms of the memory requirements…
hanugm
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