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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43 views

What is the difference between a reward and a value for a given state?

I am trying to learn reinforcement learning and I am focusing on the value iteration. I am looking at the example of grid world, and I am trying to implement it in python. While doing this, I ...
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12 views

What is the conceptual difference between convolutional neural networks and auto-encoders?

I'm familiar with Auto-Encoders and I'm about to dive into CNNs. By having a look at the most important component of a CNN, the filter: I wonder how it is different from Auto-Encoders: For me, it ...
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1answer
28 views

Is the Bandit Problem an MDP?

I've read Sutton and Barto's introductory RL book. They define a policy as a mapping from states to probabilities of selecting each possible action. If the agent is following policy $\pi$ at time $t$, ...
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37 views

What is the exact difference between distributional semantics and distributed semantics?

While studying word embeddings in natural language processing, I encountered the following statement on page 327 of the textbook Natural Language Processing by Jacob Eisenstein Distributional ...
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1answer
44 views

What is the difference between terminal state, nonterminal states and normal states?

In Sutton & Barto's Reinforcement Learning: An Introduction, page 54, the authors define the terminal state as following: Each episode ends in a special state called the terminal state But the ...
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2answers
42 views

What is the difference between “ground truth” and “ground-truth labels”?

I'm aware that the ground-truth of the example at the top left-hand corner of the image below is "zero" However, I am confused about the meaning of the terms ground truth and ground-truth ...
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1answer
34 views

Is categorical encoding a type of word embedding?

Word embedding refers to the techniques in which a word is represented by a vector. There are also integer encoding and one-hot encoding, which I will collectively call categorical encoding. I can see ...
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1answer
35 views

Where do the feature extraction and representation learning differ?

Feature selection is a process of selecting a subset of features that contribute the most. Feature extraction allows to get new features that are not actually present in the given set of features. ...
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77 views

What is the difference between ERL and EA by considering it as RL?

I am currently studying as an MSCS student and my research is based on Evolutionary Algorithm as Reinforcement Learning, and I am confused about the following terms: What is the difference between ...
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1answer
27 views

What is the difference between the “equal error rate” and “detection cost function” metrics?

I was designing a multi-speaker identification model, so I searched for some metrics that one may use. I found two metrics: EER (equal error rate) DCF (detection cost function) What is the ...
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1answer
83 views

What are the major differences between multi-armed bandits and the other well-known algorithms (DQN, A3C, PPO, etc)?

I have studied in the past different algorithms, i.e. DQN, DDQN, REINFORCE, A3C, PPO, TRPO, so on. I am doing an internship this summer where I have to use a multi-armed bandit (MAB). I am a bit ...
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40 views

What is the difference between applying shallow-learning methods repeatedly and deep learning?

In the book Deep Learning with Python, François Chollet writes (section 1.2.6, page 18) In practice, there are fast-diminishing returns to successive applications of shallow-learning methods, because ...
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61 views

Comparing heuristics in A* search and rescue operation

I was reading a research paper titled A Comparative Study of A-star Algorithms for Search and rescue in Perfect Maze (2011). I have some doubts regarding it: 1. The Evaluation Function of $\mathrm{A}^...
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Are the two do-calculus systems equivalent?

The version of the do-calculus system in The Book of Why by Judea Pearl is a little bit simpler than the original version. Are the two systems equivalent? The simple version is as follows: Rule1 ...
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1answer
67 views

What is the relation between self-taught learning and transfer learning?

I am new to transfer learning and I start by reading A Survey on Transfer Learning, and it stated the following: according to different situations of labeled and unlabeled data in the source domain, ...
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3answers
111 views

Is there a relationship between Computer Algebra and NLP?

My intuition is that there is some overlap between understanding language and symbolic mathematics (e.g. algebra). The rules of algebra are somewhat like grammar, and the step-by-step arguments get ...
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2answers
153 views

What is the difference between a language model and a word embedding?

I am self-studying applications of deep learning on the NLP and machine translation. I am confused about the concepts of "Language Model", "Word Embedding", "BLEU Score". ...
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30 views

Which method is the most efficient for memory-bounded MCTS with a transposition table?

I am building an agent for a board game that can have a relatively lot of time to think. Therefore, memory management should be efficient. I am using a transposition table, where the nodes are stored ...
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68 views

Is there any situation in which breadth-first search is preferable over A*?

Is there any situation in which breadth-first search is preferable over A*?
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1answer
220 views

What is the difference between out of distribution detection and anomaly detection?

I'm currently reading the paper Likelihood Ratios for Out-of-Distribution Detection, and it seems that their problem is very similar to the problem of anomaly detection. More precisely, given a neural ...
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2answers
65 views

Do AlphaZero/MuZero learn faster in terms of number of games played than humans?

I don't know much about AI and am just curious. From what I read, AlphaZero/MuZero outperform any human chess player after a few hours of training. I have no idea how many chess games a very talented ...
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13 views

AI generator for imaginary street maps?

Similar to This person does not exist or This artwork does not exist, how might I go about creating a This street map does not exist, including choosing an appropriate AI model and scoping features? ...
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1k views

What is the difference between Q-learning, Deep Q-learning and Deep Q-network?

Q-learning uses a table to store all state-action pairs. Q-learning is a model-free RL algorithm, so how could there be the one called Deep Q-learning, as deep means using DNN; or maybe the state-...
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1answer
63 views

Can AI be understood as a generalized statistics tool? [duplicate]

I am a (soon-to-become, to be honest) theoretical physicist. I want to learn a bit about AI. So as you know in physics we develop theories based on as few and as simple basic equations as possible ...
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1answer
145 views

What are the advantages of RL with actor-critic methods over actor-only methods?

In general, what are the advantages of RL with actor-critic methods over actor-only (or policy-based) methods? This is not a comparison with the Q-learning series, but probably a method of learning ...
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36 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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1answer
175 views

How can a probability density value be used for the likelihood calculation?

Consider our parametric model $p_\theta$ for an underlying probabilistic distribution $p_{data}$. Now, the likelihood of an observation $x$ is generally defined as $L(\theta|x) = p_{\theta}(x)$. The ...
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1answer
47 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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1answer
619 views

What are the fundamental differences between VAE and GAN for image generation?

Starting from my own understanding, and scoped to the purpose of image generation, I'm well aware of the major architectural differences: A GAN's generator samples from a relatively low dimensional ...
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60 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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509 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 ...
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1answer
101 views

Are Graph Neural Networks generalizations of Convolutional Neural Networks?

In lecture 4 of this course, the instructor argues that GNNs are generalizations of CNNs, and that one can recover CNNs from GNNs. He presents the following diagram (on the right) and mentions that it ...
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1answer
50 views

What is “Pattern Theory”?

I came across Grenander's work "Probabilities on Algebraic Structures" recently and found that much of Grenander's work focused on what he called "Pattern Theory." He's written ...
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1answer
91 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
303 views

What is the difference between the heuristic function and the evaluation function in A*?

I am reading college notes on state search space. The notes (which are not publicly available) say: To do state-search space, the strategy involves two parts: defining a heuristic function, and ...
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1answer
104 views

How are these equations of SGD with momentum equivalent?

I know this question may be so silly, but I can not prove it. In Stanford slide (page 17), they define the formula of SGD with momentum like this: $$ v_{t}=\rho v_{t-1}+\nabla f(x_{t-1}) \\ x_{t}=x_{...
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1answer
85 views

What is the difference between object tracking and trajectory prediction?

In autonomous driving, we know that the behaviour prediction module is concerned with understanding how the agents in the environment will behave. Similarly, in the perception module, the tracking ...
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1answer
104 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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1answer
43 views

What are the conceptual differences between regularisation and optimisation in deep neural nets?

I'm trying to wrap my mind around the concepts of regularisation and optimisation in neural nets, especially around their differences. In my current understanding, regularisation is intended to tackle ...
3
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1answer
93 views

Why does off-policy learning outperform on-policy learning?

I am self-studying about Reinforcement Learning using different online resources. I now have a basic understanding of how RL works. I saw this in a book: Q-learning is an off-policy learner. An off-...
5
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1answer
408 views

What is the difference between Stochastic Hill Climbing and Simulated Annealing?

I am reading about local search: hill climbing, and its types, and simulated annealing One of the hill climbing versions is "stochastic hill climbing", which has the following definition: ...
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45 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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1answer
409 views

What is the difference between the uniform-cost search and Dijkstra's algorithm?

Every computer science student (including myself, when I was doing my bachelor's in CS) probably encountered the famous single-source shortest path Dijkstra's algorithm (DA). If you also took an ...
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1answer
36 views

What is the difference between sensitivity analysis and parameter tuning?

I tried different values of genetic algorithm operators: many crossover rates from 20% to 80% many crossover rates from 1% to 20% varying the population size The study of different parameter values ...
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0answers
48 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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1answer
178 views

Why are there two versions of softmax cross entropy? Which one to use in what situation?

I have seen 2 forms of softmax cross-entropy loss and are confused by the two. Which one is the right one? For example in this Quora answer, there are 2 answers: $L(\mathbf{w})=\frac{1}{N} \sum_{n=1}^...
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1answer
124 views

Is reinforcement learning only about determining the value function?

I started reading some reinforcement learning literature, and it seems to me that all approaches to solving reinforcement learning problems are about finding the value function (state-value function ...
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3answers
123 views

What is the difference between neural networks and other ways of curve fitting?

For simplicity, let's assume we want to solve a regression problem, where we have one independent variable and one dependent variable, which we want to predict. Let's also assume that there is a ...
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67 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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36 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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