All Questions
Tagged with difference or comparison
458 questions
6
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3
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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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3
votes
0
answers
43
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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 ...
- 297
11
votes
2
answers
2k
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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 ...
- 131
4
votes
1
answer
283
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 ...
- 847
2
votes
1
answer
269
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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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4
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4
answers
5k
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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 ...
- 249
0
votes
1
answer
1k
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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 ...
- 171
2
votes
0
answers
99
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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 ...
- 1,171
1
vote
1
answer
1k
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What are the differences between 1-step SARSA and SARSA?
SARSA is on-policy, while n-step SARSA is off-policy. But when n = 1, is it like an off-policy version of SARSA? Any similarity and difference between 1-step SARSA and SARSA?
- 351
2
votes
0
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132
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What is the relationship between PAC learning and classic parameter estimation theorems?
What are the differences and similarities between PAC learning and classic parameter estimation theorems (e.g. consistency results when estimating parameters, e.g. with MLE)?
- 847
3
votes
1
answer
5k
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What is the difference between hill-climbing and greedy best-first search algorithms?
While watching MIT's lectures about search, 4. Search: Depth-First, Hill Climbing, Beam, the professor explains the hill-climbing search in a way that is similar to the best-first search. At around ...
- 1,291
2
votes
1
answer
236
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How are the Bellman optimality equations and minimax related?
Is the philosophy between Bellman equations and minimax the same?
Both the algorithms look at the full horizon and take into account potential gains (Bellman) and potential losses (minimax).
...
- 171
3
votes
2
answers
3k
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 ...
- 335
3
votes
4
answers
896
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What are the pros and cons of studying machine learning before deep learning? [duplicate]
I'm a biotech student and I'm currently working on single-particle tracking. For my work, I need to use aspects of deep learning (CNN, RNN and object segmentation) but I'm not familiar with these ...
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3
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1
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380
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 ...
- 847
2
votes
1
answer
396
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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 ...
- 41.4k
4
votes
1
answer
1k
views
What is the difference between model and data distributions?
Is there any difference between the model distribution and data distribution, or are they the same?
- 404
1
vote
2
answers
3k
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What is the relationship between the reward function and the value function?
To clarify it in my head, the value function calculates how 'good' it is to be in a certain state by summing all future (discounted) rewards, while the reward function is what the value function uses ...
- 633
1
vote
0
answers
134
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What is the difference between using dense layers as opposed to convolutional layers in my networks when dealing with images?
I am thinking about developing a GAN.
What is the difference between using dense layers as opposed to convolutional layers in my networks when dealing with images?
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1
vote
1
answer
268
views
What is relation between gradient descent and regularization in deep learning?
Gradient descent is used to reduce the loss and regularization is used to fight over-fitting.
Is there any relation between gradient descent and regularization, or both are independent of each other?...
- 1,763
2
votes
0
answers
89
views
What is the difference between training a model with RGB images and using only the color channels separately?
What is the difference between training a model with RGB images and using only the color channels separately (like only the red channel, green channel, etc.)? Would the model also learn patterns ...
- 175
1
vote
0
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173
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What are the pros and cons of deep learning and machine learning to develop a trading system?
As I want to start coding a new Trading AI this year (first based on Python and later maybe in C++) I stumbled over the following question:
Today, I would like to make a pro/contra list with you in ...
- 11
3
votes
3
answers
278
views
What is the difference between batch and mini-batch gradient decent?
I am learning deep learning from Andrew Ng's tutorial Mini-batch Gradient Descent.
Can anyone explain the similarities and dissimilarities between batch GD and mini-batch GD?
- 1,763
3
votes
0
answers
133
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Are No Free Lunch theorem and Universal Approximation theorem contradictory in the context of neural networks?
To my understanding NFL states that, we cannot have an hypothesis (let's assume it is an approximator like NN in this case) class that can't achieve certain accuracy parameters $\leq \epsilon$ with ...
user9947
0
votes
1
answer
633
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-...
- 1,763
1
vote
0
answers
75
views
Which one is better: multivariate regression with basis expansion or neural networks?
Assume we are given a training dataset $D = \{ (x_i, y_i)\}_{i=1}^{N}$.
My question is: which is better?
A multivariate regression with basis expansion with independent matrix $X$ and dependent ...
6
votes
1
answer
3k
views
What are pros and cons of Bi-LSTM as compared to LSTM?
What are the pros and cons of LSTM vs Bi-LSTM in language modelling? What was the need to introduce Bi-LSTM?
- 1,763
4
votes
0
answers
61
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What is the difference between "out-of-distribution (generalisation)" and "(meta)-transfer learning"?
I'm trying to develop a better understanding of the concept of "out-of-distribution" (generalization) in the context of Bengio's "Moving from System 1 DL to System 2 DL" and the concept of "(meta)-...
1
vote
1
answer
444
views
What is the relationship between the Q and V functions?
Suppose we have a policy $\pi$ and we use SARSA to evaluate $Q^\pi(s, a)$, where $a$ is the policy $\pi$.
Can we say that $Q^\pi(s, a) = V^\pi(s)$?
The reason why I think this can be the case is ...
- 1,291
5
votes
1
answer
551
views
What is the difference between evolutionary computation and evolutionary algorithms?
A book on evolutionary computation by De Jong mentions both the term evolutionary algorithms (EA) as well as evolutionary computation (EC). However, it remains unclear to me what the difference ...
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20
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2
answers
20k
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What are the main differences between skip-gram and continuous bag of words?
The skip-gram and continuous bag of words (CBOW) are two different types of word2vec models.
What are the main differences between them? What are the pros and cons of both methods?
- 1,763
2
votes
0
answers
262
views
What are the advantages and disadvantages of extrinsic and perplexity model evaluation in NLP?
In the video Evaluation and Perplexity by Dan Jurafsky, the author talks about extrinsic and perplexity evaluation in the context of natural language processing (NLP).
What are the advantages and ...
- 1,763
6
votes
2
answers
874
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 ...
- 193
2
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1
answer
746
views
What's the intuition behind contrastive learning?
Recently, I have seen a surge of papers w.r.t contrastive learning (a subset of semi-supervised learning).
Can anyone give a detailed explanation of this approach with its advantages/disadvantages ...
- 181
1
vote
0
answers
65
views
What are the pros and cons of the common activation functions?
I have heard that sigmoid activation functions should not be used on neural networks with many hidden layers as the gradients tend to vanish in deep networks.
When should each of the common ...
- 307
1
vote
1
answer
994
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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9
votes
4
answers
11k
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
...
- 155
8
votes
1
answer
31k
views
What is the difference between LSTM and RNN?
What is 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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1
vote
0
answers
56
views
What is the difference between an generalised estimating equation and a recurrent neural network?
What is the difference between a generalised estimating equation (GEE) model and a recurrent neural network (RNN) model, in terms of what these two models are doing? Apart from the differences in the ...
- 151
1
vote
1
answer
358
views
What is the difference between TensorFlow's callbacks and early stopping?
What is the difference between TensorFlow's callbacks and early stopping?
- 47
4
votes
1
answer
407
views
Is the minimax algorithm model-based?
Trying to get my head around model-free and model-based algorithms in RL. In my research, I've seen the search trees created via the minimax algorithm. I presume these trees can only be created with a ...
- 633
0
votes
1
answer
673
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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7
votes
1
answer
935
views
Why is the state-action value function used more than the state value function?
In reinforcement learning, the state-action value function seems to be used more than the state value function. Why is it so?
- 404
5
votes
1
answer
716
views
Is there a reason to use TensorFlow over PyTorch for research purposes?
I've been using PyTorch to do research for a while and it seems to be quite easy to implement new things with. Also, it is easy to learn and I didn't have any problem with following other researchers ...
- 1,040
3
votes
1
answer
147
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Which is a better form of regularization: lasso (L1) or ridge (L2)?
Given a ridge and a lasso regularizer, which one should be chosen for better performance?
An intuitive graphical explanation (intersection of the elliptical contours of the loss function with the ...
- 308
5
votes
1
answer
761
views
Is there a reason to choose regular momentum over Nesterov momentum for neural networks?
I've been reading about Nesterov momentum from here and it seems like a nice improvement over regular momentum with no extra cost whatsoever.
However, is this really the case? Are there instances ...
- 1,040
7
votes
4
answers
1k
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Are PAC learnability and the No Free Lunch theorem contradictory?
I am reading the Understanding Machine Learning book by Shalev-Shwartz and Ben-David and based on the definitions of PAC learnability and No Free Lunch Theorem, and my understanding of them it seems ...
- 113
2
votes
1
answer
121
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What is the difference between graph semi-supervised learning and normal semi-supervised learning?
Whenever I look for papers involving semi-supervised learning, I always find some that talk about graph semi-supervised learning (e.g. A Unified Framework for Data Poisoning Attack to Graph-based Semi-...
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5
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1
answer
2k
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Are model-free and off-policy algorithms the same?
In respect of RL, is model-free and off-policy the same thing, just different terminology? If not, what are the differences? I've read that the policy can be thought of as 'the brain', or decision ...
- 633
3
votes
2
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626
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Why are the terms classification and prediction used as synonyms in the context of deep learning?
Why are the terms classification and prediction used as synonyms especially when it comes to deep learning? For example, a CNN predicts the handwritten digit.
To me, a prediction is telling the next ...
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