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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15 views

When past states contain useful information, does A3C perform better than TD3, given that TD3 does not use an LSTM?

I am trying to build an AI that needs to have some information about the past states as well. Therefore, LSTMs are suitable for this. Now, I want to know that for a problem/game like Breakout, where ...
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1answer
38 views

What are some applications where tree models perform better than neural networks?

Neural networks are known to be better modeling techniques as compared to machine learning tree-based algorithms. Are there any exceptions to this?
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81 views

What is eager learning and lazy learning?

What is the difference between eager learning and lazy learning? How does eager learning or lazy learning help me build a neural network system? And how can I use it for any target function?
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34 views

What is the difference between Bayes-adaptive MDP and a Belief-MDP in Reinforcement Learning?

I have been reading a few papers in this area recently and I keep coming across these two terms. As far as I'm aware, Belief-MDPs are when you cast a POMDP as a regular MDP with a continuous state ...
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1answer
53 views

What is the difference between vanilla policy gradient and advantage actor-critic?

What is the difference between vanilla policy gradient (VPG) with a baseline as value function and advantage actor-critic (A2C)? By vanilla policy gradient I am specifically referring to spinning up's ...
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3answers
145 views

Why is symbolic AI not so popular as ANN but used by IBM's Deep Blue?

Everybody is implementing and using DNN with, for example, TensorFlow or PyTorch. I thought IBM's Deep Blue was an ANN-based AI system, but this article says that IBM's Deep Blue was symbolic AI. Are ...
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47 views

What are the differences between backbones, frontends, models and architectures in applied deep learning?

Context I'm trying to dive into deep learning for tasks on images, and trying to figure out how to reuse some well-known structures* that have been published, mainly on github. ( *Here, structure can ...
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31 views

Isn't it true that using max over a softmax will be much slower because there is not a smooth gradient?

Isn't it true that using max over a softmax will be much slower because there is not a smooth gradient? Max basically zeros out the gradients of all the non-maximum values. Especially at the beginning ...
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1answer
77 views

How is the reward in reinforcement learning different from the label in supervised learning problems?

How is the notion of immediate reward used in the reinforcement learning different from the notion of a label we find in the supervised learning problems?
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1answer
35 views

How exactly does nested cross-validation work?

I have trouble understanding how nested cross-validation works - I understand the need for two loops (one for selecting the model, and another for training the selected model), but why are they nested?...
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1answer
57 views

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

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

How to measure/estimate the energy consumption of CNN models during testing?

Does someone know a method to estimate / measure the total energy consumption during the test phase of the well-known CNN models? So with a tool or a power meter... MIT has already a tool to estimate ...
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1answer
27 views

How is trajectory sampling different than normal (importance) sampling in reinforcement learning?

I am using Sutton and Barto's book for Reinforcement Learning. In Chapter 8, I am having difficulty in understanding the Trajectory Sampling. I have read the particular section on trajectory sampling (...
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1answer
57 views

What is the difference between distant supervision and self-supervision?

Weak supervision is supervised learning, with uncertainty in the labeling, e.g. due to automatic labeling or because non-experts labelled the data [1]. Distant supervision [2, 3] is a type of weak ...
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1answer
41 views

Intuitively, why can the training of a neural network be formulated as a probability estimation problem?

Neural network training problems are oftentimes formulated as probability estimation problems (such as autoregressive models). How does one intuitively understand this idea?
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1answer
22 views

What are the main differences between a language model and a machine translation model?

What are the main differences between a language model and a machine translation model?
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2answers
98 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-...
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1answer
35 views

How to express $v_\pi(s)$ in terms of $q_\pi(s,a)$?

This is the exercise 3.18 in Sutton and Barto's book. The task is to express $v_\pi(s)$ using $q_\pi(s,a)$. Looking at the diagram above, the value of $q_\pi(s,a)$ at $s$ for each $a \in A$ we take ...
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1answer
58 views

What are the differences between SARSA and Q-learning?

From Sutton and Barto's book Reinforcement Learning (Adaptive Computation and Machine Learning series), are the following definitions: To aid my learning of RL and gain an intuition, I'm focusing on ...
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1answer
56 views

What is the difference between LSTM and fully connected LSTM?

I'm currently trying to understand the difference between a vanilla LSTM and a fully connected LSTM. In a paper I'm reading, the FC-LSTM gets introduced as FC-LSTM may be seen as a multivariate ...
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2answers
58 views

Can we achieve what a CNN can do with just a normal neural network?

When I was learning about neural networks, I saw that a complex neural network can understand the MNIST dataset and a simple convolution network can also understand the same. So I would like to know ...
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1answer
63 views

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

Throughout my readings, I have seen many authors using interchangeably the two terms to refer to the same thing. However, we all know about Google's first quotation of "knowledge graph" to refer to ...
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1answer
55 views

When to use NLP, NLG and NLU in conversation agents?

I had read some blogs (like 1, 2 or 3) about what the difference between all three of them is. I am trying to build an open domain conversation agent using natural language AI. That agent can do ...
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1answer
56 views

What is the difference between simulated annealing and deterministic annealing?

Not sure if this is the right place, but I was wondering if someone could briefly explain to me the differences & similarities between simulated annealing and deterministic annealing? I know that ...
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1answer
36 views

What are the differences between constraint satisfaction problems and linear programming?

I have taken an algorithms course where we talked about LP significantly, and also many reductions to LPs. As I recall, normal LP is not NP-Hard. Integer LP is NP-Hard. I am currently taking an ...
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1answer
120 views

What is the difference between one-shot learning, transfer learning and fine tuning?

Lately, there are lots of posts on one-shot learning. I tried to figure out what it is by reading some articles. To me, it looks like similar to transfer learning, in which we can use pre-trained ...
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2answers
64 views

Is there any difference between reward and return in reinforcement learning?

I am reading Sutton and Barto's book on reinforcement learning. I thought that reward and return were the same things. However, in Section 5.6 of the book, 3rd line, first paragraph, it is written: ...
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1answer
64 views

Should I use minimax or alpha-beta pruning?

Should I use minimax or alpha-beta pruning (or both)? Apparently, alpha-beta pruning prunes some parts of the search tree.
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1answer
61 views

What is the difference between reinforcement learning and evolutionary algorithms?

What is the difference between reinforcement learning (RL) and evolutionary algorithms (EA)? For some problems, you could presumably co-evolve two "species" populations using evolutionary algorithms ...
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0answers
31 views

Why do we need recurrent neural networks instead of feed-forward neural networks? [duplicate]

Why do we need recurrent neural networks instead of feed-forward neural networks? What are the advantages of RNNs compared with FFNNs?
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21 views

Is there any difference between bounded sum and bold union fuzzy set operations?

Is there any difference between bounded sum and bold union fuzzy set operations? What about the difference between bounded difference and bold intersection? In some books, I found no difference, and,...
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1answer
45 views

What is the relation between multi-agent learning and reinforcement learning?

What is the relation between multi-agent learning and reinforcement learning? Is one a sub-field of the other? For instance, would it make sense to state that your research interest are multi-agent ...
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1answer
122 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 ...
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0answers
26 views

What is a example showing that the tree-based variant for the greedy best-first search is incomplete?

I understand that a tree-based variant will have nodes repeatedly added to the frontier. How do I craft an example where a particular goal node is never found. Is this example valid. On the other ...
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1answer
36 views

What are the main differences between sparse autoencoders and convolution autoencoders?

What are the main differences and similarities between sparse autoencoders and convolution autoencoders? When should one be preferred over the other? What are their applications? (References are ...
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1answer
111 views

Why is update rule of the value function different in policy evaluation and policy iteration?

In the textbook "Reinforcement Learning: An Introduction", by Richard Sutton and Andrew Barto, the pseudo code for Policy Evaluation is given as follows: The update equation for $V(s)$ comes from the ...
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1answer
67 views

What is the difference between on-policy and off-policy for continuous environments?

I'm trying to understand RL applied to time series (so with infinite horizon) which have a continous state space and a discrete action space. First, some preliminary questions: in this case, what is ...
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24 views

What are the differences between a deep belief network, a restricted Boltzmann machine and a deep Boltzmann machine?

Can anyone list the differences between deep Belief network (DBN), restricted Boltzmann machine (RBM), deep Boltzmann machine (DBM) using simple examples? Links to other resources are also ...
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1answer
101 views

What is the difference between deep learning and shallow learning?

What is the difference between deep learning and shallow learning? What I am interested in knowing is not the definition of deep learning & shallow learning, but understanding the actual ...
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0answers
44 views

What is a Hidden Markov Model - Artificial Neural Network (HMM-ANN)?

As far as I know, neural networks have hidden computational units and HMM has hidden states. Hidden Markov Models can be used to generate a language, that is, list elements from a family of strings. ...
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2answers
177 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 ...
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0answers
18 views

What is the difference between fuzzy neural networks and adaptive neuro fuzzy inference systems?

I have, like you see, just a general question about the combination of fuzziness and neural networks. I understood it as follows Fuzzy neural networks as a hybrid system: the neural network helps me ...
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2answers
56 views

What is the difference between artificial intelligence and swarm intelligence?

Artificial intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think like humans and mimic their actions. The term may also be applied to any machine ...
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0answers
25 views

How do reinforcement learning and collaborative learning overlap?

How do reinforcement learning and collaborative learning overlap? What are the differences and similarities between these fields? I feel like the results I get via google do not make the distinction ...
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1answer
187 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 ...
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1answer
95 views

What are the differences between artificial neural networks and other function approximators?

Modern artificial neural networks use a lot more functions than just the classic sigmoid, to the point I'm having a hard time really seeing what classifies something as a "neural network" over other ...
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1answer
88 views

Are these two definitions of the state-action value function equivalent?

I have been reading the Sutton and Barto textbook and going through David Silvers UCL lecture videos on YouTube and have a question on the equivalence of two forms of the state-action value function ...
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3answers
144 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 ...
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1answer
30 views

What is the difference between the state transition of an MDP and an action-value?

Let's say we have MDP where we have a state transition matrix. How is this state transition different from action value in reinforcement learning? Is the state transition in MDP stochastic ...
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42 views

How are the classical MDP and the object-oriented MDP views different?

I've been reading the attached paper - which aims to model entities in the world as objects, including the learning agent itself! To say the least, the goal is to navigate through what seems like a ...

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