All Questions
Tagged with comparison comparison or
458 questions
1
vote
1
answer
24
views
How do neural scaling laws explain the improvements from LSTMs to Transformer based models
I was reading about a study on neural scaling laws from 2017 and they noted this as a summary. From Hestness, Joel; Narang, Sharan; Ardalani, Newsha; Diamos, Gregory; Jun, Heewoo; Kianinejad, Hassan; ...
- 279
0
votes
0
answers
37
views
When should you use a transformer and when LSTM, GRU and other Neural Networks?
There is a lot of information on the Internet that the transformer is better than RNN in everything, but is it true?
Examples:
«What if I need to translate words?»
«Generate text, images?»
«Play a ...
0
votes
2
answers
55
views
Is there any actual difference between these 2 definitions of a state value function?
The definition of the value function in TRPO paper is
\begin{align}
V_\pi(s_t) &= \mathbb{E}_{a_t,s_{t+1},\ldots} \left[ \sum_{l=0}^{\infty} \gamma^l r(s_{t+l}) \right], \\[10pt]
a_t &\sim \pi(...
- 139
0
votes
1
answer
108
views
Does Machine Learning focus on discriminative AI while Deep Learning also focus on generative AI?
I know that Deep Learning is subset of Machine learning
But is it correct that classical ML algorithms mainly focus on implementing Discriminative AI while DL algorithms implement both Generative AI ...
- 181
0
votes
2
answers
107
views
What do we mean by "AI is correlated"?
From Wikipedia
Causal AI is a technique in artificial intelligence that builds a causal model and can thereby make inferences using causality rather than just correlation. One practical use for ...
- 117
2
votes
2
answers
556
views
Is it easier to use back-propagation or genetic algorithms to teach an artificial intelligence?
I am making a very simple neural network for a school project, and I would like to know what the best and easiest way to "teach" a neural network would be. From what I know, backpropagation ...
- 23
0
votes
0
answers
21
views
Are there leaderboards/tables/stats that compare inference times between close-sourced LLMs such as GPT 3.5/4 and Claude?
https://huggingface.co/spaces/optimum/llm-perf-leaderboard is great to compare inference times between LLMs but it misses close-sourced LLMs such as GPT 3.5/4 and Claude.
- 3,267
1
vote
2
answers
1k
views
What is the difference between densenet and resnet?
Is the only difference between the two how the skip connection is combined? Resnet combines skip connections through addition and Densenet through concatenating.
The Densenet paper appears to be ...
- 233
1
vote
1
answer
98
views
Is there any advantage of genetic algorithm (or programming) over Neural Networks? [closed]
I am planning to switch from neural networks to genetic algorithms (GA) and programming (GP).
One of the main hassles of working with neural networks is that it requires a large amount of training ...
- 339
0
votes
2
answers
61
views
Should I define my problem as image segmentation or detection?
I have a problem and have to decide wether it's an object detection or object segmentation problem. I want to use Yolov8 for training. We already have hundrets of images but they aren't labeled yet. ...
- 113
1
vote
1
answer
1k
views
When to use Pruning, Quantization , Distillation and others when optimizing speed
I want to understand how to optimize models for inference speed and am seeking some advice and best practices for the same.
I am a little bit aware of the concepts of pruning, quantization, and ...
- 789
4
votes
2
answers
3k
views
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
1
vote
1
answer
133
views
Why are these two implementations of the $\epsilon$-greedy policy different?
According to the book Reinforcement Learning An Introduction, the epsilon greedy policy can generally implemented as:
$$
\pi(a|s) =
\begin{cases}
\frac{\epsilon}{|A|} + 1 - \epsilon & \text{if } ...
- 195
2
votes
1
answer
541
views
What are the similarities between Q-learning and Value Iteration?
This is the explanation of value iteration in our notes where you keep applying bellman optimality equation till it stops changing and then acting greedily wrt the value function gives the optimal ...
- 23
1
vote
1
answer
48
views
Is there validation data in K-fold cross-validation?
We know that in machine learning the dataset is divided into 3 parts: training data, validation data and test data.
On the other hand, K-fold cross-validation is defined as follows:
the dataset is ...
- 1,115
0
votes
1
answer
247
views
What is the difference between Machine Learning model, algorithm and hypothesis?
I'm fairly new to Machine Learning field and still to grasp the basics, so this question may seem very stupid, but what is the difference between Machine Learning model, algorithm and hypothesis?
Like ...
0
votes
1
answer
140
views
Which search algorithm expands nodes closest to the goal?
I want to know which search algorithm among A* and Best-First Search and Greedy First Search expands nodes closest to the goal. I have three opinions about A* and Best-First Search and Greedy First ...
- 3
0
votes
1
answer
169
views
What is the difference between A/B testing and Reinforcement Learning?
I was learning ML, and I learnt a new section called, Reinforcement Learning. After some research on web, I found that it is a trial and error technique by which ...
0
votes
1
answer
192
views
How are the intuitions and mathematics of attention mechanisms related to those of PageRank?
Excuse me if you find this question too vague and not fitting to this forum and feel free to close it. The overall goal of my question is to get a better intuition of the attention concept and ...
4
votes
1
answer
289
views
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 ...
- 454
4
votes
1
answer
2k
views
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-...
- 41
1
vote
1
answer
85
views
Are on-policy algorithms always better than off-policy ones?
I am studying RL and I have a question: Are on-policy algorithms always better than off-policy ones?
1
vote
1
answer
96
views
How are these two equations for the optimal state-value function equivalent?
By substituting the optimal policy $\pi_{\star}$ into the Bellman equation, we get the Bellman equation for $v_{\pi_{\star}}(s)=v_{\star}(s)$:
$$ v_{\star}(s) = \sum\limits_a \pi_{\star}(a|s) \sum\...
- 1,115
3
votes
1
answer
588
views
Do the terms 'sample complexity' and 'sample efficiency' mean the same thing in RL context
For example, the the paper Soft Actor-Critic:Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor, both terms are mentioned but without explaining. I have seen them in other ...
- 195
0
votes
1
answer
4k
views
What's the difference between classification and segmentation in deep learning?
What's the difference between classification and segmentation in deep learning?
In particular, can the classification loss function be used for segmentation problems?
1
vote
0
answers
38
views
What is the precise relation between Swarm Intelligence and Ensemble Methods?
I come from the machine learning side of AI, and have recently become more interested in the bio-inspired side of AI. Specifically I started reading about swarm intelligence and immediately started ...
- 11
0
votes
0
answers
50
views
Are autoencoders computationally cheaper than MLPs with the same number of neurons?
Are autoencoders computationally cheaper than other neural networks such as MLP with the same number of neurons?
I have read in some papers that autoencoders train the network faster, and I could ...
- 1
0
votes
0
answers
1k
views
What are the similarities and differences between ChatGPT and YouChat?
I have recently tried the both, and it looks to me that the both have similar capabilities.
YouChat says ChatGPT is more advanced.
YouChat has connection to the Internet, and according to it, ...
- 351
1
vote
1
answer
681
views
For specific tasks, is it better to fine-tune models on examples or just use prompting with the context of the task?
These days large language models cover a vast amount of topics and information, but I wanted to understand: For specific tasks, is it better to fine-tune models on examples or just use prompting with ...
- 113
0
votes
2
answers
909
views
Should I use multi-armed-bandits or RL for a financial time-series problem?
If we take simple financial timeseries data(stock/commodity/currency prices), State(t+1) does not depend on the action that we choose to take at State(t) as in Maze or Chess problem.
Simple example: ...
- 3
-1
votes
1
answer
452
views
Is my understanding correct regarding the difference between policy and plan?
I am confused regarding the difference between policy and plan in reinforcement learning. According to my understanding, when we calculate the value of state using Bellman equation in deterministic ...
- 111
1
vote
0
answers
94
views
How do transformers compare to CNNs in terms of compute budget (and computing time) during inference?
Transformers are data and GPU hungry during training. Is this also true at inference time? How do transformers compare to feedforward CNNs e.g., during bounding box generation at inference time? I ...
- 433
1
vote
0
answers
24
views
Is there an AI technique (or general programming technique) suitable for seeing if two articles deal with the same event?
I'm looking for a way to work out if two or more articles deal with the same event or issue and I'm not sure where to start.
For example, back in August 2022 there were a few articles on the latest ...
- 11
3
votes
2
answers
4k
views
What is the difference between A2C and Q-Learning, and when to use one over the other?
I'm trying to get an accurate answer about the difference between A2C and Q-Learning. And when can we use each of them?
- 33
2
votes
1
answer
283
views
Why and when do we use ReLU over tanh activation function?
I was reading LeCun Efficient Backprop and the author repeated stressed the importance of average the input patterns at 0 and thus justified the usage of tanh sigmoid. But if tanh is good then how ...
0
votes
0
answers
62
views
As someone starting out in RL, could you help me understand the differences between actor-only, critic-only, and actor-critic methods?
I have been reading some medium articles and these three methods pop up a lot. I am wondering what the differences between these are, what are the advantages of one over the other, etc. Also from my ...
- 101
3
votes
1
answer
9k
views
Does SAC perform better than PPO in sample-expensive tasks with discrete action spaces?
I am currently using Proximal Policy Optimization (PPO) to solve my RL task. However, after reading about Soft Actor-Critic (SAC) now I am unsure whether I should stick to PPO or switch to SAC. ...
- 53
1
vote
1
answer
982
views
Why does mean episode reward during training differ dramatically from "manual" runs of the trained model on same data?
I am training an RL agent, using PPO, on a time-series environment that comes from a tabular dataset. The possible scores during an episode goes from -1 to positive infinity (though realistically, I ...
- 362
2
votes
0
answers
111
views
When are traditional image processing methods preferable to machine learning and why?
By traditional image processing I understand, e. g. using filters to improve the image, extracting edges and then classifying objects using template matching.
My current decision criteria are:
large ...
- 21
10
votes
1
answer
9k
views
What is the difference between the triplet loss and the contrastive loss?
What is the difference between the triplet loss and the contrastive loss?
They look same to me. I don't understand the nuances between the two. I have the following queries:
When to use what?
What ...
- 373
1
vote
0
answers
117
views
Is item-based collaborative filtering the same thing as content-based filtering?
According to this Google dev page
content-based filtering
Uses similarity between items to recommend items similar to what the
user likes.
collaborative filtering
Uses similarities between queries ...
- 11
0
votes
1
answer
80
views
Is there a way to improve the low-quality data?
I'm on a robotics team and we've been tasked to write a program to differentiate between a live and dead fish. We've been given ~15 minutes of training footage and it's absolutely terrible. It's low ...
user55176
1
vote
2
answers
68
views
What are all the possible usages of 'multilayer perceptron'?
The term 'multilayer perceptron' has been used in literature in various ways in the literature.
I am presenting some of them below
As a feed-forward neural network [1].
As a fully connected feed-...
- 3,990
2
votes
0
answers
61
views
What are the specific differences between vision transformers variants?
I have tried 4 different types of attacks on vision transformers (ViT small and tiny, DeiT small and tiny) but the attack successes on smaller versions are higher than the tiny versions. My ...
- 31
2
votes
2
answers
5k
views
What is the difference between features and inputs in machine learning?
I have seen many places that features and inputs have been used interchangeably when talking about machine learning especially deep neural networks. I want to know if they are indeed the same thing or ...
- 145
2
votes
2
answers
3k
views
What are the differences between BLEU and METEOR?
I am trying to understand the concept of evaluating the machine translation evaluation scores.
I understand how what BLEU score is trying to achieve. It looks into different n-grams like BLEU-1,BLEU-2,...
- 373
1
vote
2
answers
1k
views
What is the difference between a policy and rewards?
I don't understand the difference between a policy and rewards. Sure, a policy tells us what to do, but isn't the output of a neural network trained on rewards basically a policy (i.e. choose the ...
0
votes
1
answer
1k
views
What is the difference between CNN-LSTM and RNN?
I'm starting to study RNN for a project of video prediction, but I encounter these CNN-LSTM models. Initially, I thought that is another name for RNN, but I think I get it wrong. Since I'm a beginner ...
3
votes
3
answers
1k
views
Why are Siamese Neural Networks used instead of a single neural network?
Siamese Neural Networks are a type of neural network used to compare two instances and infer if they belong to the same object. They are composed by two parallel identical neural networks, whose ...
- 63
2
votes
0
answers
28
views
What are the benefits of using spectral k-means over simple k-means?
I have understood why k-means can get stuck in local minima.
Now, I am curious to know how the spectral k-means helps to avoid this local minima problem.
According to this paper A tutorial on Spectral,...
- 121