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?

69 questions with no upvoted or accepted answers
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657 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 ...
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348 views

What is the difference between GAT and GaAN?

I was looking at two papers Graph Attention Networks (GAT) by Petar Veličković and GaAN: Gated Attention Networks for Learning on Large and Spatiotemporal Graphs by Jiani Zhang. I'm trying to ...
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1answer
280 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
65 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
91 views

How can we derive a Convolution Neural Network from a more generic Graph Neural Network?

Convolution Neural Network (CNNs) operate over strict grid-like structures ($M \times N \times C$ images), whereas Graph Neural Networks (GNNs) can operate over all-flexible graphs, with an undefined ...
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33 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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34 views

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)-...
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125 views

What are the differences between CRF and HMM?

What I know about CRF is that they are discriminative models, while HMM are generative models, but, in the inference method, both use the same algorithm, that is, the Viterbi algorithm, and forward ...
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214 views

What is the relation between the definition of learnability of Vapnik and Gold and learnability of neural networks?

Gold showed that a language can be learned only if it contains a finite set of sentences. We know that deep neural networks can implement any function. Does this contradict the Gold's result? What ...
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31 views

How and why do state-of-the-art models in medical segmentation differ from general segmentation models?

I am just getting into medical image segmentation and have been able to understand the state-of-the-art architectures, like Double UNet, UNet++, and Multiresunet. What I haven't understood yet: Why ...
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50 views

What is the return-to-go in reinforcement learning?

In reinforcement learning, the return is defined as some function of the rewards. For example, you can have the discounted return, where you multiply the rewards received at later time steps by ...
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26 views

What is the difference between text-based image retrieval and natural language object retrieval?

I'm working on creating a model that locates the object in the scene (2D image or 3D scene) using a natural language query. I came across this paper on natural language object retrieval, which ...
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66 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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24 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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53 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 ...
2
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1answer
146 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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25 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 ...
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62 views

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 ...
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1answer
199 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 ...
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107 views

What is the difference between using a backbone architecture and transfer learning?

I'm super new to deep learning and computer vision, so this question may sound dumb. In this link (https://github.com/GeorgeSeif/Semantic-Segmentation-Suite), there are pre-trained models (e.g., ...
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47 views

Can the importance sampling estimator have a non-stationary behaviour policy even if the target policy is stationary?

The inverse propensity score (IPS) estimator, which is used for off-policy evaluation in a contextual bandit problem, is well explained in the paper Doubly Robust Policy Evaluation and Optimization. ...
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41 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 ...
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51 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 ...
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38 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 ...
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60 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 ...
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1answer
136 views

Does GraphSage use hard attention?

I was reading the recent paper Graph Representation Learning via Hard and Channel-Wise Attention Networks, where the authors claim that there is no hard attention operator for graph data. From my ...
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428 views

What are the differences between Deepfakes, FaceSwap and Face2Face?

I've compared videos manipulated with three different automated face manipulation methods: Deepfakes, Face2Face, and FaceSwap. Surprisingly, I found the output videos quite different: Deepfakes and ...
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132 views

What are the key differences between cellular neural network and convolutional neural network?

What are the key differences between cellular neural networks and convolutional neural networks in terms of working principle, implementation, potential performance, and applicability?
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52 views

Is there a mechanism in the human brain that works analog to LSTMs?

Is there a mechanism in the human brain that works analog to LSTMs? Is there a biological/neuroscientific interpretation of LSTMs and recurrent neural networks? How do long-term and short-term ...
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89 views

What is the difference between visible and hidden units in Boltzmann machines?

What is the difference between visible and hidden units in Boltzmann machines? What are their purposes?
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35 views

How is few-shot learning different from transfer learning?

To my understanding, transfer learning helps to incorporate data from other related datasets and achieve the task with less labelled data (maybe in 100s of images per category). Few-shot learning ...
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39 views

What are the pros and cons of 3D CNN and 2D CNN combined with optical flow for action recognition?

For action recognition or similar tasks, one can either use 3D CNN or combine 2D CNN with optical flow. See this paper for details. Can someone tell the pros/cons of each, in terms of accuracy, cost ...
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42 views

How exactly is hindsight experience replay related to potential-based reward shaping?

One of the reviewers of the HER paper (which was accepted as a NIPS conference paper) wrote Overall, I'd say that it's not a huge/deep idea, but a very nice addition to the learning toolbox. When it ...
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46 views

What is the difference between exploitation and exploration in the context of optimization?

In the paper Moth-flame optimization algorithm: A novel nature-inspired heuristic paradigm (2015, published in Knowledge-Based Systems) The test functions are divided to three groups: unimodal, multi-...
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178 views

What is the difference between derivation and entailment?

In section 7.3 of the book Artificial Intelligence: A Modern Approach (3rd edition), it's written An inference algorithm that derives only entailed sentences is called sound or truth-preserving. The ...
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42 views

What are the disadvantages of actor-only methods with respect to value-based ones?

While the advantages of actor-only algorithms, the ones that search directly the policy without the use of the value function, are clear (possibility of having a continuous action space, a stochastic ...
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38 views

Given the same features, do logistic regression and neural networks produce the same output?

I have a binary classification problem. I have variables (features) var1, var2, var3, ..., var14. Using these variables (aka features) in a logistic regression, I get their weights. If I use the same ...
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24 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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33 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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33 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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0answers
33 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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0answers
31 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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56 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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55 views

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)?
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76 views

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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100 views

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 in 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 ...
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59 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 ...
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0answers
67 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 ...
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38 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 ...
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33 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 ...