Questions tagged [comparison]

For questions that involve the comparison of two AI concepts, terms or expressions. An example of such a question is: how does machine learning compare to deep learning?

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1answer
1k views

What are the differences between a knowledge base and a knowledge graph?

During my readings, I have seen many authors using the two terms interchangeably, i.e. as if they refer to the same thing. However, we all know about Google's first quotation of "knowledge graph&...
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1answer
27 views

What is the difference between the positional encoding techniques of the Transformer and GPT?

I know the original Transformer and the GPT (1-3) use two slightly different positional encoding techniques. More specifically, in GPT they say positional encoding is learned. What does that mean? ...
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89 views

What is the difference between a vision transformer and image-based relational learning?

I am trying to figure out the difference between the architecture used in this and this paper. It looks like both used multi-headed self-attention and therefore should be the same in principle.
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460 views

Do Seq2Seq models and the Bidirectional RNN do the same thing?

It seems to me that Seq2Seq models and Bidirectional RNNs try to do the same thing. Is that true? Also, when would you recommend one setup over another?
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26 views

In this example of fuzzy c-means, what is the difference between "sigma" and "center" for the clusters?

In this example, what exactly do "Cluster" and "Sigma" mean? (They chose random coordinates for the three centroids of the groups) Centers: Cluster centers, returned as a ...
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1answer
50 views

When to use the state value function $V(s)$ and when to use the state-action value function $Q(s, a)$?

I saw the difference between value function $V(s)$ and $Q(s, a)$. But when do I use each one? When I coded in Matlab I only used $Q(s, a)$ directly (as I was thinking of a tabular approach). So, when ...
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1answer
189 views

How can neural networks approximate any continuous function but have $\mathcal{VC}$ dimension only proportional to their number of parameters?

Neural networks typically have $\mathcal{VC}$ dimension that is proportional to their number of parameters and inputs. For example, see the papers Vapnik-Chervonenkis dimension of recurrent neural ...
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10answers
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What is the difference between artificial intelligence and machine learning?

These two terms seem to be related, especially in their application in computer science and software engineering. Is one a subset of another? Is one a tool used to build a system for the other? What ...
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1answer
73 views

Closed networks vs Networks with a removed delay to predict new data

I've come across two types of neural networks to predict, both from Matlab, the closed structure and the net that removes one delay to find new data. From Matlab's app generated scripts we see: % ...
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2answers
3k views

What is the difference between search and planning?

I'm reading the book Artificial Intelligence: A Modern Approach (by Stuart Russell and Peter Norvig). However, I don't understand the difference between search and planning. I was more confused when I ...
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2answers
3k views

Difference between Assisted Intelligence and Artificial intelligence [closed]

What is the difference between Assisted Intelligence and Artificial Intelligence? And why is former seen as an opportunity and the latter as a threat?
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1answer
41 views

How will MLOps and lifelong learning be complementary?

According to [1], in MLOps, continuous training is a new property, unique to ML systems, that's concerned with automatically retraining and serving the models. While lifelong/incremental learning ...
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1answer
790 views

What are the consequences of layer norm vs batch norm?

I'll start with my understanding of the literal difference between these two. First, let's say we have an input tensor to a layer, and that tensor has dimensionality $B \times D$, where $B$ is the ...
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1answer
48 views

Is my understanding on "smooth approximation" correct?

Consider the following details regarding Softplus activation function $$\text{Softplus}(x) = \dfrac{\log(1+e^{\beta x})}{\beta}$$ SoftPlus is a smooth approximation to the ReLU function and can be ...
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1answer
82 views

Is there any difference between an objective function and a value function?

I found the usage of both objective function and value function in the same context. Context #1: In the paper titled Generative Adversarial Nets by Ian J. Goodfellow et al. We simultaneously train G ...
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1answer
96 views

What is the difference between parametric and non-parametric models?

A model can be classified as parametric or non-parametric. How are models classified as parametric and non-parametric models? What is the difference between the two approaches?
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0answers
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What is the difference between Probabilistic Graphical models and Graph Neural networks?

While going over PGMs and GNNs, it seems like both leverage the graph data structure. The former has been used to represent causal associations (among other things), while the latter has a varied set ...
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1answer
60 views

What is the difference between the "equal error rate" and "detection cost function" metrics?

I was designing a multi-speaker identification model, so I searched for some metrics that one may use. I found two metrics: EER (equal error rate) DCF (detection cost function) What is the ...
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1answer
66 views

How is the VAE related to the Autoencoding Variational Bayes (AEVB) algorithm?

I am familiar with the variational autoencoder, but not totally clear on what exactly the AEVB is. In the original VAE paper (by Kingma and Welling), he uses both the terms variational autoencoder and ...
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1answer
4k views

What is the difference between a receptive field and a feature map?

In a CNN, the receptive field is the portion of the image used to compute the filter's output. But one filter's output (which is also called a "feature map") is the next filter's input. What's the ...
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1answer
129 views

What is the difference between exhaustive nearest neighbor search and k-nearest neighbour search?

I have two lists of feature vectors calculated from pre-trained CNN for image retrieval task: Query: FV_Q and Reference FV_R. <...
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1answer
138 views

What's the difference between domain randomization and domain adaptation?

In my understanding, domain randomization is one method of diversifying the dataset to achieve a better shot at domain adaptation. Am I wrong?
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2answers
174 views

When to use Value Iteration vs. Policy Iteration

Both value iteration and policy iteration are General Policy Iteration (GPI) algorithms. However, they differ in the mechanics of their updates. Policy Iteration seeks to first find a completed ...
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2answers
754 views

Why do value iteration and policy iteration obtain similar policies even though they have different value functions?

I am trying to implement value and policy iteration algorithms. My value function from policy iteration looks vastly different from the values from value iteration, but the policy obtained from both ...
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2answers
121 views

How can the policy iteration algorithm be model-free if it uses the transition probabilities?

I'm actually trying to understand the policy iteration in the context of RL. I read an article presenting it and, at some point, a pseudo-code of the algorithm is given : What I can't understand is ...
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1answer
996 views

How does the Dempster-Shafer theory differ from Bayesian reasoning?

How does the Dempster-Shafer theory differ from Bayesian reasoning? How do these two methods handle uncertainty and compute posterior distributions?
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2answers
212 views

When should I use Genetic Algorithms as opposed to Particle Swarm Optimization?

For which problems are Genetic Algorithms more suitable than Particle Swarm Optimization, and vice-versa? Are there any guidelines?
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1answer
2k views

What’s the difference between LSTM and RNN?

What's the difference between LSTM and RNN? I know that RNN is a layer used in neural networks, but what exactly is an LSTM? Is it also a layer with the same characteristics?
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1answer
2k views

How does best-first search differ from hill-climbing?

How does best-first search differ from hill-climbing?
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What is the difference between "Syllogism" and "Law of Syllogism"?

The logical arguments are the basis for Artificial Intelligence. That is why I picked AI community to ask my question. Reading from Wikipedia, A syllogism is a kind of logical argument that applies ...
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2answers
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Why has the cross-entropy become the classification standard loss function and not Kullback-Leibler divergence?

The cross-entropy is identical to the KL divergence plus the entropy of the target distribution. The KL divergence equals zero when the two distributions are the same, which seems more intuitive to me ...
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1answer
714 views

What are hyper-heuristics, and how are they different from meta-heuristics?

I wanted to know what the differences between hyper-heuristics and meta-heuristics are, and what their main applications are. Which problems are suited to be solved by hyper-heuristics?
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65 views

A comparison of Expert Systems and Machine Learning approaches in terms of run-time-efficiency and time/space complexity

For part of a paper I am writing on Clinical Decision Support Systems (computer-aided medical decision making, e.g. diagnosis, treatment), I am trying to compare Expert Systems with systems based on ...
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1answer
61 views

Is "kernel" different from "filter" in convolutional neural networks?

Recently I asked a question on how a convolution 2d layer changes an RGB image into a grayscale image. Assume that our task is to convert an RGB image into a grayscale image. I use to believe that ...
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4answers
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What is the difference between training and testing in reinforcement learning?

In reinforcement learning (RL), what is the difference between training and testing an algorithm/agent? If I understood correctly, testing is also referred to as evaluation. As I see it, both imply ...
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1answer
140 views

What's the difference between architectures and backbones?

In the paper "ForestNet: Classifying Drivers of Deforestation in Indonesia using Deep Learning on Satellite Imagery", the authors talk about using: Feature Pyramid Networks (as the ...
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1answer
52 views

When should we use CNN instead of MLP?

Is CNN only applicable to time-series data or image data? When should we use CNN instead of MLP?
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1answer
67 views

Why should one ever use ReLU instead of PReLU?

To me, it seems that PReLU is strictly better than ReLU. It does not have the dying ReLU problem, it allows negative values and it has trainable parameters (which are computationally negligible to ...
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2answers
116 views

What is the difference between automatic transcription and automatic speech recognition?

What is the difference between automatic transcription and automatic speech recognition? Are they the same? Is my following interpretation correct? Automatic transcription: it converts the speech to ...
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1answer
69 views

Can I treat "experience" in reinforcement learning as "training data" in statistical learning?

Statistics is a branch of mathematics that extracts useful information from data. The data is generally called as "training data" in statistical (machine) learning. Consider the following ...
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1answer
72 views

Are there any advantages of using rules-based approaches versus models for detecting spam?

Suppose that we have unlabeled data. That is, all we have are a collection of emails and want to determine whether any of them is spam or not. Let's say we have $1,000$ rules to determine whether a ...
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1answer
44 views

Does average loss function in GAN training is just an approximation of value function and does not ensure convergence of generator and discriminator?

The value function on which convergence has been proved by the original paper of GAN is $$\min_G \max_DV(D, G) = \mathbb{E}_{x ∼ P_{data}}[\log D(x)] + \mathbb{E}_{z ∼ p_z}[log (1 - D(G(z)))]$$ and ...
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1answer
329 views

What is the difference between the US and global edition of the AIMA book by Russell and Norvig?

The book Artificial Intelligence: A Modern Approach by Russell and Norvig has two editions: global and the US. It looks like these two are generally the same, but have some differences in the order of ...
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1answer
32 views

Can I always interpret features as random variables in machine learning safely?

Consider the following statements from Chapter 5: Machine Learning Basics from the book titled Deep Learning (by Aaron Courville et al.) Machine learning tasks are usually described in terms of how ...
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1answer
28 views

What is the borderline between unsupervised learning and regular algorithms?

Unsupervised learning using neural networks is clearly machine learning since it is utilising neural nets. However, some algorithms, k-means clustering, for example, are considered unsupervised ...
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1answer
129 views

What are the pros and cons of supervised, semi-supervised and unsupervised relation extraction in NLP?

I am following the NLP course taught by Dan Jurafsky. In the video lectures Supervised Relation Extraction and Semi Supervised and Unsupervised Relation Extraction Jurafsky explains supervised, semi-...
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0answers
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Why does one-step TD strengthen only the last action of the sequence of actions that led to the high reward, while n-step TD the last n actions?

In the caption of figure 7.4 (p. 147) of Sutton & Barto's book (2nd edition), it's written The one-step method strengthens only the last action of the sequence of actions that led to the high ...
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1answer
380 views

What are the differences between Bytenet and Wavenet?

I recently read Bytenet and Wavenet and I was curious why the first model is not as popular as the second. From my understanding, Bytenet can be seen as a seq2seq model where the encoder and the ...
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1answer
18 views

Why would the Dice coefficient be more suitable than mutual information when you don't want 0-0 matches to be significant?

I'm confused about the interpretation and assumptions of the Dice coefficient versus the more popular measure mutual information. I'm specifically referencing its use in hierarchical semantic network ...
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1answer
1k views

What is the difference between reinforcement learning and evolutionary algorithms?

What is the difference between reinforcement learning (RL) and evolutionary algorithms (EA)? I am trying to understand the basics of RL, but I do not yet have practical experience with RL. I know ...

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