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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2
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1answer
26 views

Do we need an explicit policy to sample $A'$ in order to compute the target in SARSA or Q-learning?

I would much appreciate if you could point me in the right direction regarding this question about targets for SARSA and Q-learning (notation: $S$ is the current state, $A$ is the current action, $R$ ...
5
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1answer
41 views

What is the intuition behind TD($\lambda$)?

I'd like to better understand temporal-difference learning. In particular, I'm wondering if it is prudent to think about TD($\lambda$) as a type of "truncated" Monte Carlo learning?
1
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1answer
37 views

What is the difference between the epsilon greedy and softmax policies?

Could someone explain to me which is the key difference between the epsilon greedy policy and the softmax policy? In particular in the contest of SARSA and Q-Learning algorithms. I understood the main ...
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1answer
75 views

In which cases is the categorical cross-entropy better than the mean squared error?

In my code, I usually use the mean squared error (MSE), but the TensorFlow tutorials always use the categorical cross-entropy (CCE). Is the CCE loss function better than MSE? Or is it better only in ...
2
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1answer
64 views

What are the differences between TensorFlow and PyTorch?

What are the differences between TensorFlow and PyTorch, both in terms of performance and functionality?
2
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0answers
33 views

How can I compare EEG data with accelerometer data in 1 algorithm?

I have frequency EEG data from fall and non-fall events and I am trying to incorporate it with accelerometer data that was collected at the same time. One approach is, of course, to use two separate ...
2
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2answers
85 views

Why are traditional ML models still used over deep neural networks?

I'm still on my first steps in the Data Science field. I played with some DL frameworks, like TensorFlow (pure) and Keras (on top) before, and know a little bit of some "classic machine learning" ...
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0answers
16 views

What's the difference between semi-supervised VAEs and conditional VAEs?

Can someone explain the difference? I'm assuming the difference is just that the neural nets representing the encoder and decoder are trained in a semi-supervised manner in semi-supervised VAE, which ...
2
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1answer
64 views

What is the difference between Sutton's and Levine's REINFORCE algorithm?

I followed the videos/slides of Berkley RL course, but now I am a bit confused when implementing it. Please see the picture below. In particular, what does $i$ represent in the REINFORCE algorithm? ...
6
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2answers
277 views

Is word embedding a form of feature extraction?

Feature extraction is a concept concerning the translation of raw data into the inputs that a particular machine learning algorithm requires. These derived features from the raw data that are actually ...
2
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1answer
61 views

What is the difference between linear and non-linear regression?

In machine learning, I understand that linear regression assumes that parameters or weights in equation should be linear. For Example: $$y = w_1x_1 + w_2x_2$$ is a linear equation where $x_1$ and $...
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0answers
25 views

What is the difference between principal component analysis and singular value decomposition in image processing?

What is the difference between principal component analysis and singular value decomposition in image processing? Which one performs better, and why?
0
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1answer
61 views

What are the characteristics of a deep learning AI?

I have experience in making several Artificial Neural Networks and some programs which may be classified as an Artificial Intelligence by using Tensorflow.js and Brain.js. In order to produce ...
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0answers
27 views

How would you differentiate between different on-policy reinforcement learning algorithms?

How would you differentiate between different on-policy reinforcement learning algorithms?
2
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4answers
104 views

What is the difference between artificial intelligence and artificial neural networks?

I have made several neural networks by using Brain.Js and TensorFlow.js. What is the difference between artificial intelligence and artificial neural networks?
1
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1answer
58 views

What is the difference between game theory and machine learning?

What is the difference between game theory and machine learning? I had gone through the papers Deep Learning for Predicting Human Strategic Behavior, by Jason Hartford et al., and When Machine ...
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0answers
29 views

How to extract face details from a image

I am trying to make a face login application that authenticates the user when matching the registered face and the given face. currently, the issue is I cant extract the face descriptions from the ...
3
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1answer
28 views

Can non-sequential deep learning models outperform sequential models in time series forecasting?

Can a CNN (or other non-sequential deep learning models) outperform LSTM (or other sequential models) in time series data? I know this question is not very specific, but I experienced this when ...
4
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2answers
69 views

What is the difference between genetic algorithms and evolutionary game theory algorithms?

What is the difference between genetic algorithms and evolutionary game theory algorithms?
2
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0answers
32 views

What is the difference between evolutionary game theory and meta-heuristics?

Here is a list of meta-heuristic algorithms Ant colony optimization, Ant lion optimizer, Artificial bee colony algorithm, Bat algorithm, Cat swarm optimization, Crow search algorithm, Cuckoo ...
5
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3answers
211 views

Is k-fold cross-validation more effective than splitting the dataset into training and test datasets to prevent overfitting?

I want to prevent my model from overfitting. I think that k-fold cross-validation (because it is doing this each time with different datasets) may be more effective than splitting the dataset into ...
3
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1answer
173 views

What's the difference between RMSE and Euclidean distance, and when to use a custom loss? [closed]

I'm searching for a loss function that fits my project. Actually, I have two questions, but they are in the same direction. I take a look at the definition of the root mean squared error (RMSE) and ...
8
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5answers
6k views

What does AI software look like, and how is it different from other software?

What does AI software look like? What is the major difference between AI software and other software?
11
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1answer
5k views

Are humans superior to machines in chess?

A friend of mine, who is an International Master at chess, told me that humans were superior to machines provided you didn't impose the time constraints that exist in competitive chess (40 moves in 2 ...
3
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2answers
100 views

What is the difference between reinforcement learning and AutoML?

My vague understanding of reinforcement learning (RL) is that it's very similar to supervised learning except that it updates on a continuous feed of data/activity, this to me sounds very similar to ...
5
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2answers
53 views

Perfect Information and Imperfect Information Games

In perfect information games, the agent can see all the moves performed in the past. Besides, it can observe the next action that will be put into practice by the opponent. In this case, can we say ...
3
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1answer
86 views

Which books or papers clearly explain the relation between Ising models and deep neural networks?

I am looking for a book or paper which clearly explains the relationship between Ising models and deep neural networks. Can anyone provide any references?
5
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1answer
77 views

Are deep learning models more prone to overfitting than machine learning ones?

In my opinion, deep learning algorithms and models (that is, multi-layer neural networks) are more sensitive to overfitting than machine learning algorithms and models (such as the SVM, random forest, ...
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0answers
25 views

What is the complexity of policy gradient algorithms compared to discrete action space algorithms?

I am using a policy gradient algorithm (actor-critic) for wireless networks. The policy gradient-based algorithm helps because it considers continuous action space. But how much does a policy ...
2
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0answers
21 views

What is the difference between the ant system and the max-min ant system?

I'm studying ant colony optimization. I'm trying to understand the difference between the ant system (AS) and the max-min ant system (MMAS) approaches. As far as I found out, the main difference ...
3
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1answer
58 views

Combining machine learning with languages like ProLog?

There are mainly two different areas of AI at the moment. There is the "learning from experience" based approach of neural networks. And there is the "higher logical reasoning" approach, with ...
3
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0answers
132 views

What are the differences between Yolo v1 and CenterNet?

I recently read a new paper (late 2019) about a one-shot object detector called CenterNet. Apart from this, I'm using Yolo (V3) one-shot detector, and what surprised me is the close similarity between ...
1
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1answer
62 views

When should I use a linear activation instead of ReLU?

I have read this post: How to choose an activation function?. There is enough literature about activation functions, but when should I use a linear activation instead of ReLU? What does the author ...
3
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1answer
53 views

How do I determine the most appropriate classifier for a certain problem?

Consider a Bayesian classifier used in spam e-mail filtering. It converts an e-mail to a vector, most of the time using the bag-of-words method. Although it learns first before getting employed, it ...
1
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1answer
82 views

An “elevator pitch” breakdown of areas of applications for Reinforcement Learning & Neural Networks vs. Genetic Algorithms

I'm looking for an "elevator pitch" breakdown of areas of applications for Reinforcement Learning & Neural Networks vs. Genetic Algorithms, both actual and theoretical. Links are welcome, but ...
1
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3answers
168 views

Is machine learning required for deep learning?

The answers to this Quora question say it's OK to ignore machine learning and start right away with deep learning. Is machine learning required or is useful for understanding (theoretically and ...
2
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1answer
53 views

What is the difference between a semantic network and an ontology?

I am not getting exactly the difference between semantic networks and ontology. I do not find a proper article explaining about ontology in the semantic network. According to me, I think that the ...
1
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1answer
53 views

What is the difference between the definition of a stationary policy in reinforcement learning and contextual bandit?

A stationary policy is a function that maps a state to a probability distribution of actions. In a contextual bandit problem, a state itself does not include the history. But in a reinforcement ...
3
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1answer
38 views

What are the differences between stability and convergence in reinforcement learning?

The terms are mentioned in the paper: “An Emphatic Approach to the Problem of off-Policy Temporal-Difference Learning.” (Sutton, Mahmood, White; 2016) and more, of course. In which paper, they ...
5
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1answer
89 views

How do we determine whether a heuristic is better than another?

I am trying to solve a Maze puzzle using the A* algorithm. I am trying to analyze the algorithm based on different applicable heuristics. Currently, I explored the Manhattan and Euclidean distances. ...
1
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0answers
53 views

Is Value Iteration better than Policy Iteration for first few iterations?

In Policy Iteration (PI), the action generated by the policy, whether it's optimal or not w.r.t the current value function $v(s)$. Whereas, in Value Iteration, the action is greedily generated w.r.t ...
3
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1answer
89 views

Why are model-based methods more sample efficient than model-free methods?

Why do model-based methods use fewer samples than model-free methods? Here, I'm specifically referring to model-based methods in which we have to learn a policy and model. I can only think of two ...
3
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1answer
111 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 ...
2
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1answer
40 views

Can supervised learning be recast as reinforcement learning problem?

Let's assume that there is a sequence of pairs $(x_i, y_i), (x_{i+1}, y_{i+1}), \dots$ of observations and corresponding labels. Let's also assume that the $x$ is considered as independent variable ...
1
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1answer
140 views

What is the difference between classical and quantum machine learning?

By classical, I mean the current Machine learning Algorithms we have, according to the current status of Machine Learning field, some we have or might have not gained the in-depth aspects which will/...
2
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0answers
29 views

What is the difference between Squeeze-and-excite and bottleneck modules from Mobilenet v2?

Squezee-and-excite networks introduced SE blocks, while MobileNet v2 introduced linear bottlenecks. What is the effective difference between these two concepts? Is it only implementation (depth-wise ...
5
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2answers
240 views

What is the difference between graph convolution in the spatial vs spectral domain?

I've been reading different papers regarding graph convolution and it seems that they come into two flavors: spatial and spectral. From what I can see the main difference between the two approaches is ...
4
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4answers
133 views

Why isn't conditional probability sufficient to describe causality?

I read these comments from Judea Pearl saying we don't have causality, physical equations are symmetric, etc. But the conditional probability is clearly not symmetric and captures directed ...
1
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1answer
71 views

What is the difference between 2d vs 3d convolutions?

I was trying to understand the definition of 2d convolutions vs 3d convolutions. I saw the "simplest definition" according to Pytorch and it seems the following: 2d convolutions map $(N,C_{in},H,W) \...
1
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1answer
29 views

What is the difference between multi-agent and multi-modal systems?

The Wikipedia definitions are as follows Multi-agent systems - A multi-agent system is a computerized system composed of multiple interacting intelligent agents. Multi-modal interaction - Multimodal ...