Artificial Intelligence Stack Exchange Community Digest

Top new questions this week:

Why does a neural network struggle to solve this simple problem?

Consider the following problem: Given a vector x of size dim with values between 0 and 1 (exclusive), determine if …

neural-networks tensorflow multilayer-perceptrons binary-classification

asked by Daniel Score of 3

Why do adversarial attacks work on CNNs if they classify images as humans do?

A common illustration on how CNN works is as follows: www.researchgate.net/figure/Learned-features-from-a-Convolutional-Neural-Network_fig1_319253577. It seems to suggest that CNN in …

convolutional-neural-networks computer-vision adversarial-ml adversarial-attacks

asked by Sam Score of 2

Should DQN/PPO be used for state spaces that are not that large?

I’m interested in trying out Q-learning to solve a problem where I already have a simulation of the environment that can run at about 100,000 fps or steps/sec. Its also continuous with no terminal …

reinforcement-learning deep-rl dqn markov-decision-process proximal-policy-optimization

asked by gameveloster Score of 2 answered by Minh-Long Luu Score of 3

Why is $\sum_{s} \eta(s)$ a constant of proportionality in the proof of the policy gradient theorem?

In Sutton and Barto’s book (incompleteideas.net/book/bookdraft2017nov5.pdf), a proof of the policy gradient theorem is provided on pg. 269 for an episodic case and a start state policy …

policy-gradients proofs sutton-barto policy-gradient-theorem

asked by jwl17 Score of 2 answered by Hadar Sharvit Score of 0

InstructGPT: What is the sigma in the loss function and why log() is being used?

InstructGPT: What is the sigma in the loss function and why log() is being used?

reinforcement-learning machine-learning open-ai chat-bots chatgpt

asked by Nathan B Score of 1

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 …

reinforcement-learning comparison terminology sample-efficiency sample-complexity

asked by Sam Score of 1 answered by nbro Score of 2

How can i create a new language model for language other than english?

I have large set of corpus for all literature in ‘Tamil’ language, i am trying to create a document retrieval engine through simple natural language. Since the corpus is huge, its hard to do a …

natural-language-processing language-model

asked by Thiyaga B Score of 1

Greatest hits from previous weeks:

What is non-Euclidean data?

What is non-Euclidean data? Here are some sub-questions Where does this type of data arise? I have come across this term in the context of geometric deep learning and graph neural networks. …

deep-learning definitions geometric-deep-learning graph-neural-networks non-euclidean-data

asked by nbro Score of 23 answered by brazofuerte Score of 13

What is self-supervised learning in machine learning?

What is self-supervised learning in machine learning? How is it different from supervised learning?

machine-learning comparison supervised-learning self-supervised-learning representation-learning

asked by nbro Score of 91 answered by nbro Score of 92

Why is Python such a popular language in the AI field?

First of all, I’m a beginner studying AI and this is not an opinion-oriented question or one to compare programming languages. I’m not implying that Python is the best language. But the fact is that …

machine-learning tensorflow python programming-languages

asked by Douglas Ferreira Score of 64 answered by Ugnes Score of 45

How do I compute the structural similarity between sentences?

I am working on a problem where I need to determine whether two sentences are similar or not. I implemented a solution using BM25 algorithm and wordnet synsets for determining syntactic & …

natural-language-processing python similarity

asked by Shubham Tiwari Score of 13 answered by Oliver Mason Score of 2

Where can I find the original paper that introduced RNNs?

I was able to find the original paper on LSTM, but I was not able to find the paper that introduced “vanilla” RNNs. Where can I find it?

recurrent-neural-networks long-short-term-memory reference-request papers

asked by Ahsan Tarique Score of 16 answered by David Nemeskey Score of 11

What is an objective function?

Local search algorithms are useful for solving pure optimization problems, in which the aim is to find the best state according to an objective function. My question is what is the objective function?

terminology objective-functions optimization local-search meta-heuristics

asked by Abbas Ali Score of 5 answered by nbro Score of 6

What are the differences between A* and greedy best-first search?

What are the differences between the A* algorithm and the greedy best-first search algorithm? Which one should I use? Which algorithm is the better one, and why?

algorithm search comparison a-star

asked by Marosh Fatima Score of 11 answered by nbro Score of 11

Can you answer this question?

Giving Specified Data a Larger Value/Weight in a Model

I’m in the process of creating a model to classify an occupational code based on a job title & description. I have a large sample of labelled data to achieve this. The government has a resource …

natural-language-processing classification weights text-classification

asked by Ryley Keegan Score of 1