All Questions

I recently read a paper on community detection in networks. In the paper EdMot: An Edge Enhancement Approach for Motif-aware Community Detection, the authors consider the "lower-order structure" of ...

I read this In Google AI blog: link: https://ai.googleblog.com/2017/08/transformer-novel-neural-network.html S1 : " the Transformer can learn to immediately attend to the word “river” and make this ...

What I did: Created a population of 2D legged robots in a simulated environment. Found the best motor rotation values to make the robots move rightward, using an objective function with Differential ...

I'm interested in learning about Neural Networks and implementing them. I'm particularly interested in GANs and LSTM networks. I understand perceptrons and basic Neural Network configuration (sigmoid ...

The author explains in 2.2 Action-Value Methods: To roughly assess the relative effectiveness of the greedy and $\varepsilon $-greedy methods, we compared them numerically on a suite of test ...

I wonder if anyone knows a database (preferably free) of images of different classes of people (age, gender) but with entire bodies shown on the pictures taken from different angles (mostly front and ...

People say embedding is necessary in NLP because if using just the word indices, the efficiency is not high as similar words are supposed to be related to each other. However, I still don't truly get ...

Usually, it's very complicated to program a real time strategy game from scratch. Notable examples like Lemmings or Starcraft are software projects with a large amount of codelines. A much easier ...

I wanted to know about Intelligent reflecting surface (IRS) technology. what is the application of IRS in wireless communication? what are the competitive advantages over existing technologies?

If a policy is fixed, it is said that an MDP becomes an MRP. Why is this so? Aren't the transitions and rewards still parameterized by the action and current state? In other words, aren't the ...

Intuitively, I understand that having an unbiased estimate of a policy is important because being biased just means that our estimate is distant from the truth value. However, I don't understand ...

My understanding of the vanishing gradient problem in deep networks is that as backprop progresses through the layers the gradients become small, and thus training progresses slower. I'm having a hard ...

The No Free Lunch (NFL) theorem states (see the paper Coevolutionary Free Lunches by David H. Wolpert and William G. Macready) any two algorithms are equivalent when their performance is averaged ...

I have a set of integers [$c_1$, $c_2$, $c_3$, ... , $c_N$]. A non-negative integer D, greater than a certain threshold, divides each 𝑐𝑖 and leaves remainder 𝑟𝑖,i.e., $r_i$ can be written as $r_i=...

I am trying to train a cnn-lstm model, my sample image sizes are 640x640. I have a GTX 1080 ti 11GB. I am using Keras with tensorflow backend. Here is the model. ...

GPU are available in 6,8,&11 Gigabyte increments. I would like to understand the thought process and questions should be asked when deciding which of the 3 memory sizes is to be chosen. The ...

I have CNN model to classify 2 classes. (Yes or No) I use categorical_crossentropy loss and softmax activation at the end. For input I use image with all 3 channels, for output I use One hot encoded ...

pjreddie's official darknet version (link from official website here) has been forked several times. In particular I've come accross AlexeyAB's fork through this tutorial. I assume the tutorial's ...

I have implemented a neural network from scratch (only using numpy) and I am having problems understanding why the results are so different between stochastic/minibatch gradient descent and batch ...

I'm currently writing a program using keras (python 3) to play a game similar to Atari games, only in this one there are objects moving in the screen in different angles and directions (in most of ...

The technical challenge of introducing rail-guided vehicles is much lower compared to self-driving cars. Automated subway lines can be formalized as a graph. in which the edges are frequented by a ...

I am going through Russel and Norvig's AI A Modern Approach 3rd Edition. I was reading the A* algorithm and it reads A* Graph Search Version is optimal when heuristic is consistent and Tree Search ...

The following X-shape alternated pattern can be separated quite well and super fast by K-nearest Neighbour algorithm (go to http://ml-playground.com to test it): However, DNN seems to face great ...

A while ago I came across a paper for image classification that utilized both label distribution and one-hot encoded labels to classify images. An image has a label distribution for all classes (4 ...

So I wrote a convolutional neural network for a binary image classification. I have around 5300 images for each class which I thought would be enough to at least give me a good accuracy on the ...

I have a use case where the state of the environment could change due to random events in between time steps that the agent takes actions. For example, at t1, the agent takes action a1 and is given ...

There are many datasets for person reidentification. I want to train a robust person re-identification neural network. Therefore I want to ask about best person re-identification dataset.

Sort of a conceptual question here. I was implementing a SOM algorithm to better understand its variations and parameters and got curious about one bit: the BMU (best matching unit == the neuron that ...

I am looking for a GAN paper I have read a while ago, but unfortunately cannot find it again. I think it compared GANs and other methods (like CVAEs) w.r.t. how they handle multi-modal data, not sure ...

Let's assume I have a CNN model trained to categorize some objects on the images. By using this model I find more categorized images. If I now retrain this model on data set that consists old set and ...

I was following some examples to get familiar with tensorflow LSTM related api, but noticed that all LSTM initialization functions require only num_units parameter which denotes number of hidden units ...

Discussing the video More Parkour Atlas a friend asked how the robot's movement where so similar to the one from a real human and wondering how this is achieve? To my knowledge this is not something ...

I've started getting into object detection in image. I have YOLOv3 neural network with Darknet framework. The network is pre-trained from COCO data set. Now I need to do some transfer learning in ...

I'm using Q-learning with some extensions such as noisy linear layers, n-steps and double DQN. The training, however, isn't that successful, my rewards are descreasing over time after a steep ...

Let's call our dataset splits train/test/evaluate. We're in a situation where we require months of data so we prefer to use the evaluation dataset as infrequently as possible to avoid polluting our ...

As computers are getting bigger better and faster, the concept of what constitutes a single datum is changing. For example, in the world of pen-and-paper, we might take readings of temperature over ...

I have a use case where the set of actions is different for different states. Is the agent aware of what actions are valid for which states or is the agent only aware of the entire action space (in ...

I'm wondering if there is a NN that can achieve the following task: Output a unit vector that is parallel to the input vector. i.e., input a vector $\mathbf{v}\in\mathbb{R}^d$, output $\mathbf{v}/\|\...

My weights go from being between 0 and 1 at initialisation to exploding into the tens of thousands in the next iteration. In the 3rd iteration they become so large that only arrays of nan values are ...

I was thinking about different neural network topologies for some applications. However, I am not sure how this would affect the efficiency of hardware acceleration using GPU/TPU/some other chip. If, ...

I found the following neural network cheat sheet (Cheat Sheets for AI, Neural Networks, Machine Learning, Deep Learning & Big Data). What are all these different kinds of neural networks used ...

Is randomness (either true randomness or simulated randomness) necessary for AI? If true, does it mean "intelligence comes from randomness"? If not, can a robot lacking the ability to generate random ...

I have a book containing lots of puzzles with instructions like: ...

I'm not sure what this type of data is called, so I will give an example of the type of data I am working with: A city records its inflow and outflow of different types of vehicles every hour. More ...

After looking around the internet (including this paper, I cannot seem to find a satisfactory explanation of the Average Recall (AR) metric. On the COCO website, it describes AR as: "the maximum ...

I have the following problem. There is a software that I've written some time ago. Users enter customer's data in the system and there is a limited number of things (actions) that they can do/add - ...

When we test a new optimization algorithm, what the process that we need to do?For example, do we need to run the algorithm several times, and pick a best performance,i.e., in terms of accuracy, f1 ...

I know recurrent neural networks for example LSTM is one of them. After LSTM different variants of LSTM have come for example GRU. I don't know about newer RNN like LSTM and GRU, so I decided to ask ...

I want to use a GAN for sequence prediction, in a similar way that we use RNNs for sequence prediction. I want to test its performance in comparison with RNNs. Is there a GAN that can be used for ...

I want to train a person detector for MOTChallenge dataset, but I want to avoid using the dataset as training set for my detector. Therefore, I want to use another dataset or combination of several ...