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?

Filter by
Sorted by
Tagged with
0
votes
0answers
16 views

Would a model-based RL algorithm perform better that a model-free one, in the air traffic control sequencing simulation field? [closed]

I am learning RL now. When I start to run my algorithm (PPO) for air traffic control sequencing, it gets trapped into local optimality. Will it be better when I choose to use a model-based RL method, ...
0
votes
0answers
11 views

How to determine the most appropriate metaheuristic for a problem?

I have a scheduling problem. but I don't know how to determine its complexity (NP-hard, NP-complete)? How could we justify the choice of a metaheuristic instead of other for a scheduling problem i.e. ...
2
votes
1answer
59 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 ...
2
votes
0answers
29 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 ...
2
votes
0answers
16 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 ...
1
vote
2answers
34 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 ...
0
votes
0answers
29 views

What is the difference between derivation and entailment?

Here is the (maybe abridged) definition from the book - Artificial Intelligence, a modern approach An inference algorithm 𝑖 is sound or truth-preserving if it derives only entailed sentences It is ...
2
votes
1answer
50 views

What's the difference between estimation and approximation error?

I'm unable to find online, or understand from context - the difference between estimation error and approximation error in the context of machine learning (and, specifically, reinforcement learning). ...
1
vote
0answers
39 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 ...
2
votes
1answer
51 views

What is the difference between parametric and non-parametric models?

A model can be classified as parametric or non-parametric. How are models classified as parametric and non-parametric models? What is the difference between the two approaches?
1
vote
1answer
27 views

What are examples of under-parametrization and over-parametrization in machine learning? [duplicate]

Today, I heard from a colleague that traditional ML works with under-parametrization while deep learning works with over-parametrization. Are there examples to illustrate the meaning of these two ...
0
votes
0answers
32 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 ...
6
votes
1answer
86 views

Why are neural networks preferred to other classification functions optimized by gradient decent

Consider a neural network, e.g. as presented by Nielsen here. Abstractly, we just construct some function $f: \mathbb{R}^n \to [0,1]^m$ for some $n,m \in \mathbb{N}$ (i.e. the dimensions of the input ...
9
votes
2answers
798 views

What is the difference between active learning and online learning?

The definitions for these 2 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 2? Is ...
1
vote
1answer
54 views

How is BERT different from the original transformer architecture?

As far as I can tell, BERT is a type of Transformer architecture. What I do not understand is: How is Bert different from the original transformer architecture? What tasks are better suited for BERT,...
4
votes
1answer
60 views

Can you convert a MDP problem to a Contextual Multi-Arm Bandits problem?

I'm trying to get a better understanding of Multi-Arm Bandits, Contextual Multi-Arm Bandits and Markov Decision Process. Basically, Multi-Arm Bandits is a special case of Contextual Multi-Arm Bandits ...
3
votes
1answer
1k views

What are the differences between Q-Learning and A*?

Q-learning seems to be related to A*. I am wondering if there are (and what are) the differences between them.
5
votes
2answers
76 views

Why are policy iteration and value iteration studied as separate algorithms?

In Sutton and Barto's book about reinforcement learning, policy iteration and value iterations are presented as separate/different algorithms. This is very confusing because policy iteration includes ...
1
vote
0answers
21 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 ...
1
vote
1answer
51 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?
4
votes
1answer
94 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?
1
vote
0answers
39 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 ...
2
votes
1answer
93 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 ...
5
votes
3answers
171 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 ...
0
votes
0answers
49 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 ...
1
vote
0answers
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 ...
2
votes
1answer
88 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?
2
votes
1answer
39 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?...
0
votes
1answer
118 views

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

How does best-first search differ from hill-climbing?
1
vote
0answers
29 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 ...
1
vote
1answer
32 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 (...
1
vote
1answer
75 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 ...
1
vote
1answer
43 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?
0
votes
1answer
26 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?
2
votes
2answers
136 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-...
2
votes
1answer
51 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 ...
0
votes
1answer
70 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 ...
2
votes
1answer
87 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 ...
1
vote
2answers
62 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 ...
2
votes
1answer
72 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 ...
1
vote
1answer
62 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 ...
1
vote
1answer
60 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 ...
2
votes
1answer
41 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 ...
2
votes
1answer
291 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 ...
4
votes
2answers
77 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: ...
1
vote
1answer
74 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.
2
votes
1answer
67 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 ...
2
votes
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?
0
votes
0answers
28 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,...
1
vote
1answer
49 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 ...

1
2 3 4 5
7