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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79
votes
3answers
70k views

What is self-supervised learning in machine learning?

What is self-supervised learning in machine learning? How is it different from supervised learning?
4
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3answers
6k views

What is the difference between a stochastic and a deterministic policy?

In reinforcement learning, there are the concepts of stochastic (or probabilistic) and deterministic policies. What is the difference between them?
4
votes
2answers
542 views

Do convolutional neural networks perform convolution or cross-correlation?

Typically, people say that convolutional neural networks (CNN) perform the convolution operation, hence their name. However, some people have also said that a CNN actually performs the cross-...
64
votes
6answers
55k views

What's the difference between model-free and model-based reinforcement learning?

What's the difference between model-free and model-based reinforcement learning? It seems to me that any model-free learner, learning through trial and error, could be reframed as model-based. In ...
5
votes
1answer
227 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 ...
91
votes
10answers
15k views

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 ...
3
votes
1answer
308 views

Why do we need convolutional neural networks instead of feed-forward neural networks?

Why do we need convolutional neural networks instead of feed-forward neural networks? What is the significance of a CNN? Even a feed-forward neural network will able to solve the image classification ...
36
votes
5answers
66k views

What is the difference between a convolutional neural network and a regular neural network?

I've seen these terms thrown around this site a lot, specifically in the tags convolutional-neural-networks and neural-networks. I know that a neural network is a system based loosely on the human ...
15
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1answer
14k views

How does LSTM in deep reinforcement learning differ from experience replay?

In the paper Deep Recurrent Q-Learning for Partially Observable MDPs, the author processed the Atari game frames with an LSTM layer at the end. My questions are: How does this method differ from the ...
20
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3answers
2k views

How are Artificial Neural Networks and the Biological Neural Networks similar and different?

I've heard multiple times that "Neural Networks are the best approximation we have to model the human brain", and I think it is commonly known that Neural Networks are modelled after our brain. I ...
4
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1answer
7k views

How do I show that uniform-cost search is a special case of A*?

How do I show that uniform-cost search is a special case of A*? How do I prove this?
3
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4answers
659 views

What is the fundamental difference between an ML model and a function?

A model can be roughly defined as any design that is able to solve an ML task. Examples of models are the neural network, decision tree, Markov network, etc. A function can be defined as a set of ...
12
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2answers
3k views

What is a recurrent neural network?

Surprisingly, this wasn't asked before - at least I didn't find anything besides some vaguely related questions. So, what is a recurrent neural network, and what are their advantages over regular (or ...
18
votes
1answer
24k views

What is the difference between tree search and graph search?

I have read various answers to this question at different places, but I am still missing something. What I have understood is that a graph search holds a closed list, with all expanded nodes, so ...
6
votes
1answer
4k views

What is the difference between a stationary and a non-stationary policy?

In reinforcement learning, there are deterministic and non-deterministic (or stochastic) policies, but there are also stationary and non-stationary policies. What is the difference between a ...
3
votes
1answer
281 views

Is there any difference between a control and an action in reinforcement learning?

There are reinforcement learning papers (e.g. Metacontrol for Adaptive Imagination-Based Optimization) that use (apparently, interchangeably) the term control or action to refer to the effect of the ...
36
votes
2answers
14k views

What is the relation between Q-learning and policy gradients methods?

As far as I understand, Q-learning and policy gradients (PG) are the two major approaches used to solve RL problems. While Q-learning aims to predict the reward of a certain action taken in a certain ...
44
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3answers
23k views

What is the difference between strong-AI and weak-AI?

I've heard the terms strong-AI and weak-AI used. Are these well defined terms or subjective ones? How are they generally defined?
30
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2answers
1k views

How is a deep neural network different from other neural networks?

How is a neural network having the "deep" adjective actually distinguished from other similar networks?
11
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5answers
8k views

What is the fundamental difference between CNN and RNN?

What is the fundamental difference between convolutional neural networks and recurrent neural networks? Where are they applied?
14
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2answers
8k views

What is the difference between reinforcement learning and optimal control?

Coming from a process (optimal) control background, I have begun studying the field of deep reinforcement learning. Sutton & Barto (2015) state that particularly important (to the writing of the ...
12
votes
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?
8
votes
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 ...
6
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6answers
12k views

What is the difference between artificial intelligence and robots?

What is the difference between artificial intelligence and robots?
4
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4answers
1k views

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 ...
21
votes
4answers
56k views

Why does C++ seem less widely used than Python in AI?

I just want to know why do machine learning engineers and AI programmers use languages like Python to perform AI tasks and not C++, even though C++ is technically a more powerful language than Python.
15
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2answers
1k views

When is deep learning overkill?

For example, for classifying emails as spam, is it worthwhile - from a time/accuracy perspective - to apply deep learning (if possible) instead of another machine learning algorithm? Will deep ...
7
votes
3answers
36k views

What are the differences between A* and greedy best-first search?

What are the differences between the A* algorithm and the greedy best-first search algorithm? Which one should I use? Which algorithm is the better one, and why?
13
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4answers
8k 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?
7
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3answers
5k views

What are the differences between transfer learning and meta learning?

What are the differences between meta-learning and transfer learning? I have read 2 articles on Quora and TowardDataScience. Meta learning is a part of machine learning theory in which some ...
19
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5answers
3k views

What is the difference between machine learning and deep learning?

Can someone explain to me the difference between machine learning and deep learning? Is it possible to learn deep learning without knowing machine learning?
13
votes
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 ...
10
votes
1answer
933 views

Why is the merged neural network of AlphaGo Zero more efficient than two separate neural networks?

AlphaGo Zero contains several improvements compared to its predecessors. Architectural details of Alpha Go Zero can be seen in this cheat sheet. One of those improvements is using a single neural ...
16
votes
3answers
8k views

What is the difference between actor-critic and advantage actor-critic?

I'm struggling to understand the difference between actor-critic and advantage actor-critic. At least, I know they are different from asynchronous advantage actor-critic (A3C), as A3C adds an ...
13
votes
2answers
3k views

What is the difference between active learning and online learning?

The definitions for these two appear to be very similar, and frankly, I've been only using the term "active learning" the past couple of years. What is the actual difference between the two? ...
11
votes
1answer
767 views

Are Q-learning and SARSA the same when action selection is greedy?

I'm currently studying reinforcement learning and I'm having difficulties with question 6.12 in Sutton and Barto's book. Suppose action selection is greedy. Is Q-learning then exactly the same ...
10
votes
2answers
5k views

Why do we prefer ReLU over linear activation functions?

The ReLU activation function is defined as follows $$y = \operatorname{max}(0,x)$$ And the linear activation function is defined as follows $$y = x$$ The ReLU nonlinearity just clips the values ...
9
votes
4answers
4k views

When to choose Stochastic Hill Climbing over Steepest Hill Climbing?

Stochastic Hill Climbing generally performs worse than Steepest Hill Climbing, but what are the cases in which the former performs better?
7
votes
2answers
789 views

What are the differences in scope between statistical AI and classical AI?

What are the differences in scope between statistical AI and classical AI? Real-world examples would be appreciated.
6
votes
1answer
8k views

How is iterative deepening A* better than A*?

The iterative deepening A* search is an algorithm that can find the shortest path between a designated start node and any member of a set of goals. The A* algorithm evaluates nodes by combining the ...
5
votes
4answers
6k views

What is the difference between "mutation" and "crossover"?

In the context of evolutionary computation, in particular genetic algorithms, there are two stochastic operations "mutation" and "crossover". What are the differences between them?
5
votes
1answer
814 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 ...
3
votes
2answers
545 views

Apart from the state and state-action value functions, what are other examples of value functions used in RL?

In reinforcement learning, we often define two functions, the state-value function $$V^\pi(s) = \mathbb{E}_{\pi} \left[\sum_{k=0}^{\infty} \gamma^{k}R_{t+k+1} \Bigg| S_t=s \right]$$ and the state-...
6
votes
2answers
2k views

What is the difference between learning without forgetting and transfer learning?

I would like to incrementally train my model with my current dataset and I asked this question on Github, which is what I'm using SSD MobileNet v1. Someone there told me about learning without ...
6
votes
2answers
850 views

What is the difference between 'prediction' and 'control' problem in the context of Reinforcement Learning?

What is the difference between the term 'prediction'/value estimation in RL as compared to the 'control' problem? Are there scenarios in RL where the problem cannot be distinctly categorised into ...
4
votes
3answers
406 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" ...
3
votes
1answer
268 views

What is the difference between image processing and computer vision?

What is the difference between image processing and computer vision? They are apparently both used in artificial intelligence.
2
votes
1answer
194 views

Is RL just a less rigorous version of stochastic approximation theory?

After reading some literature on reinforcement learning (RL), it seems that stochastic approximation theory underlies all of it. There's a lot of substantial and difficult theory in this area ...
2
votes
2answers
155 views

When should one prefer using Total Variational Divergence over KL divergence in RL

In RL, both the KL divergence (DKL) and Total variational divergence (DTV) are used to measure the distance between two policies. I'm most familiar with using DKL as an early stopping metric during ...
12
votes
2answers
7k views

What is the difference between artificial intelligence and computational intelligence?

Having analyzed and reviewed a certain amount of articles and questions, apparently, the expression computational intelligence (CI) is not used consistently and it is still unclear the relationship ...