Community Digest

Top new questions this week:

How to implement taylor expansion of progressive Convolutional NN?

I intend to implement CNN like progressively expanded neural network in Keras. The basic idea is the first input node can be decomposed into multiple nodes with different orders and coefficient, then ...

deep-learning convolutional-neural-networks keras image-recognition  
asked by Dan 4 votes

How is the state-visitation frequency computed in "Maximum Entropy Inverse Reinforcement Learning"?

I am trying to understand the formulation of the maximum entropy Inverse RL method by Brian Ziebart. Particularly, I am stuck on how to understand the computation of state - visitation frequencies. ...

reinforcement-learning markov-decision-process papers  
asked by calveeen 3 votes

What are the challenges faced by using NLP to convert mathematical texts into formal logic?

From what I've figured (a) converting mathematical theorems and proofs from English to formal logic is a straightforward job for mathematicians with sufficient background, except that it takes time. ...

natural-language-processing math logic natural-language-understanding automated-theorem-proving  
asked by ghosts_in_the_code 3 votes

Why do we need both the validation set and test set?

I know that this has been asked a hundred times before, however, I was not able to find a question (and an answer) which actually answered what I wanted to know, respectively, which explained it in a ...

neural-networks machine-learning ai-design datasets hyperparameter-optimization  
asked by Golo Roden 3 votes
answered by Edoardo Guerriero 3 votes

Before GAN, what are the commonly used techniques for image-to-image translation?

As per a post, image-to-image translation is a type of CV problem. I guess I understand the concept of image-to-image translation. I am aware that GANs(generative adversarial networks) are good ...

computer-vision  
asked by WXJ96163 3 votes
answered by Aniket Velhankar 2 votes

What is the intuition behind grid-based solutions to POMDPs?

After spending some time reading about POMDP, I'm still having a hard time understanding how grid-based solutions work. I understand the finite horizon brute-force solution, where you have your ...

markov-decision-process pomdp  
asked by FourierFlux 3 votes
answered by nbro 3 votes

Is maximum likelihood estimation meaningless for a dataset of only outliers?

From my understanding, maximum likelihood estimation chooses the set of parameters for the estimator that maximizes likelihood with the ground truth distribution. I always interpreted it as the ...

machine-learning math statistical-ai cross-entropy maximum-likelihood  
asked by ashenoy 3 votes

Greatest hits from previous weeks:

What is the difference between "mutation" and "crossover"?

In the context of evolutionary computation, in particular genetic algorithms, there are two stochastic operations "mutation" and "crossover". What are the differences between them?

genetic-algorithms evolutionary-algorithms comparison crossover mutation  
asked by Abbas Ali 4 votes
answered by nbro 5 votes

Understanding GAN loss function

I'm struggling to understand the GAN loss function as provided in Understanding Generative Adversarial Networks (a blog post written by Daniel Seita). In the standard cross-entropy loss, we have an ...

neural-networks machine-learning deep-learning loss-functions generative-adversarial-networks  
asked by tryingtolearn 18 votes
answered by Douglas Daseeco 7 votes

Can a neural network be used to predict the next pseudo random number?

Is it possible to feed a neural network the output from a random number generator and expect it learn the hashing (or generator) function, so that it can predict what will be the next generated ...

neural-networks machine-learning deep-learning prediction randomness  
asked by AshTyson 17 votes
answered by Demento 13 votes

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 4 votes
answered by nbro 4 votes

Can LSTM Nets be speed up by GPU?

I am training LSTM Nets with Keras on a small mobile GPU. The speed on GPU is slower then on CPU. I found some articles that say that it is hard to train LSTMs (RNNs) on GPUs because the training ...

tensorflow keras long-short-term-memory  
asked by Dieshe 6 votes
answered by Dieshe 4 votes

Are neural networks prone to catastrophic forgetting?

Imagine you show a neural network a picture of a lion 100 times and label with "dangerous", so it learns that lions are dangerous. Now imagine that previously you have shown it millions of images of ...

neural-networks machine-learning theory incremental-learning catastrophic-forgetting  
asked by zooby 42 votes
answered by nbro 44 votes

Why is search important in AI?

Why is search important in AI? What kinds of search algorithms are used in AI? How do they improve the result of an AI?

search  
asked by Zoltán Schmidt 9 votes
answered by NietzscheanAI 6 votes

Can you answer these questions?

Alternatives to U-Net for biomedical image segmentation

Soon I will be working on biomedical image segmentation (microscopy images). There will be a small amount of data (a few dozens at best). My question is really straightforward: is there a neural ...

neural-networks deep-learning convolutional-neural-networks image-segmentation  
asked by Nuwanda 1 vote
answered by Paul Higazi 0 votes

How can I find the appropriate reward value for my reinforcement learning problem?

I am wondering how can I find the appropriate reward value for each specific problem. I know this is a highly empirical process, but I am sure that the value is not set totally at random. I want to ...

reinforcement-learning ai-design rewards  
asked by Saeid Ghafouri 1 vote

How can I add logic for invalid moves when using stable-baselines in OpenAI's gym?

I want to integrate my environment into the OpenAI's gym and then use the stable baselines library for training it. The learning method in the stable baseline is with one-line learning and you don't ...

reinforcement-learning open-ai gym  
asked by Saeid Ghafouri 1 vote
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