All Questions
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458 questions
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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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5
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How is simulated annealing better than hill climbing methods?
In hill climbing methods, at each step, the current solution is replaced with the best neighbour (that is, the neighbour with highest/smallest value). In simulated annealing, "downhills" moves are ...
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What is the difference between an on-policy distribution and state visitation frequency?
On-policy distribution is defined as follows in Sutton and Barto:
On the other hand, state visitation frequency is defined as follows in Trust Region Policy Optimization:
$$\rho_{\pi}(s) = \sum_{t=0}^...
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Why should one ever use ReLU instead of PReLU?
To me, it seems that PReLU is strictly better than ReLU. It does not have the dying ReLU problem, it allows negative values and it has trainable parameters (which are computationally negligible to ...
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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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Why are model-based methods more sample efficient than model-free methods?
Why do model-based methods use fewer samples than model-free methods? Here, I'm specifically referring to model-based methods in which we have to learn a policy and model. I can only think of two ...
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2
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628
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What is the difference between return and expected return?
At a time step $t$, for a state $S_{t}$, the return is defined as the discounted cumulative reward from that time step $t$.
If an agent is following a policy (which in itself is a probability ...
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Why would LDA have performed much better than SVM and Naive Bayes in diagnosing ADHD?
In a final project in diagnosing Attention deficit hyperactivity disorder (ADHD) using Machine Learning, we obtained parameters from real patients. We used this data and got much higher success rates ...
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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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3
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Are Convolutional Neural Networks better than existing image recognition libraries that don't use CNNs?
Are Convolutional Neural Networks summarily better than pattern recognition in all existing image processing libraries that don't use CNN's? Or are there still hard outstanding problems in image ...
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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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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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In which cases is the categorical cross-entropy better than the mean squared error?
In my code, I usually use the mean squared error (MSE), but the TensorFlow tutorials always use the categorical cross-entropy (CCE). Is the CCE loss function better than MSE? Or is it better only in ...
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2
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Are there any learning algorithms as powerful as "deep" architectures?
This article suggests that deep learning is not designed to produce the universal algorithm and cannot be used to create such a complex systems.
First of all it requires huge amounts of computing ...
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4
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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?
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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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What are the differences between seq2seq and encoder-decoder architectures?
I've read many tutorials online that use both words interchangeably. When I search and find that they are the same, why not just use one word since they have the same definition?
user78615
4
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2
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Do convolutional neural networks also have recurrent connections? [duplicate]
I asked my self this simple question while reading "Comment Abuse Classification with Deep Learning" by Chu and Jue. Indeed, they say at the end of the that
It is clear that RNNs, specifically ...
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3
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290
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Is Deep Learning the repeated application of Linear Regression?
Is Deep Learning the repeated application of Linear Regression?
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1
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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 getting new features that are not actually present in the given set of features.
...
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4
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2
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Why is it harder to achieve good results using neural network based algorithms for multi step time series forecasting?
There are different kinds of machine learning algorithms, both univariate and multivariate, that are used for time series forecasting: for example ARIMA, VAR or AR.
Why is it harder (compared to ...
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What are the differences between softmax regression and logistic regression (other than when the number of classes is 2)?
I read about softmax from this article. Apparently, these 2 are similar, except that the probability of all classes in softmax adds to 1. According to their last paragraph for ...
user9947
4
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2
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642
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What's the difference between biological and artificial evolution?
I am trying to understand the difference between biological and artificial evolution. If we look at it in terms of genetics, in both of them, the selection operation is a key term.
What's the ...
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4
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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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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?
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Which books or papers clearly explain the relation between Ising models and deep neural networks?
I am looking for a book or paper which clearly explains the relationship between Ising models and deep neural networks.
Can anyone provide any references?
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What is the difference between a problem representation and problem modelling?
As far as I know, a problem representation is the formulation of the problem in a way that it can be programmed and therefore solved (for example, you can represent the $N$-queens problem by using an ...
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How to decide whether a problem needs to be solved algorithmically or with machine learning techniques?
There are problems (e.g. this one or this other one) that could potentially be solved easily using traditional algorithmic techniques. I think that training a neural network (or any other machine ...
user9947
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2
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1k
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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 ...
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1
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358
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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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462
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What is the difference between genetic algorithms and evolutionary game theory algorithms?
What is the difference between genetic algorithms and evolutionary game theory algorithms?
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What's the difference between RMSE and Euclidean distance, and when to use a custom loss? [closed]
I'm searching for a loss function that fits my project. Actually, I have two questions, but they are in the same direction. I take a look at the definition of the root mean squared error (RMSE) and ...
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Is there any difference between a control and an action in reinforcement learning?
There are reinforcement learning papers (e.g. Metacontrol for Adaptive Imagination-Based Optimization) that use (apparently, interchangeably) the term control or action to refer to the effect of the ...
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4
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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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4
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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 ...
4
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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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4
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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 ...
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What is the difference between learning and non-learning agents?
What is the difference between learning agents and other types of agents?
In what ways learning agents can be applied? Do learning agents differ from deep learning?
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What is the difference between a feed-forward neural network and a liquid state machine?
I have used a FFNN and LSM to perform the same task, namely, to predict the sentence "How are you". The LSM gave me more accurate results than FFNN. However, the LSM did not produce perfect prediction ...
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1
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What is the difference between pixel-based object recognition and feature-based object recognition?
From my understanding and text I found in research papers online :
Pixel-based object recognition: neural networks are trained to locate individual objects based directly on pixel data.
Feature-based ...
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4
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1
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How does Monte-Carlo Tree Search Compare to MCMC?
Monte-Carlo Tree Search was the method used for AlphaGo my understanding is: it would randomly search the state space of possible moves where the probability of choosing a move was proportional to the ...
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1
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What's the difference between GPT3.5 and InstructGPT?
I read about the different model series in GPT3.5 here - https://platform.openai.com/docs/models/gpt-3-5
At the beginning of the page, it mentions to look at https://platform.openai.com/docs/model-...
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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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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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What is the difference between a distribution model and a sampling model in Reinforcement Learning?
The book from Sutton and Barto, Reinforcement Learning: An Introduction, define a model in Reinforcement Learning as
something that mimics the behavior of the environment, or more generally, that ...
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2
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What is the difference between Sentiment Analysis and Emotion Recognition?
I found Sentiment Analysis and Emotion Recognition as two different categories on paperswithcode.com. Should both be the same as my understanding? If not what's the difference?
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What is the difference between backpropagation and predictive coding?
Reading the high-level descriptions of backpropagation and predictive coding, they don't sound so drastically different. What is the key difference between these techniques?
I am currently reading ...
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1
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255
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Is there any relation between the recursive neural network and recurrent neural network?
Recurrent neural networks, abbreviated as RNNs, are widely used in deep learning literature, especially for text processing.
Are they related to recursive neural networks in any way?
I am asking for ...
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0
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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)-...
4
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617
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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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