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1,386 questions with no upvoted or accepted answers
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11
votes
3answers
860 views

What topologies are largely unexplored in machine learning?

Geometry and AI Matrices, cubes, layers, stacks, and hierarchies are what we could accurately call topologies. Consider topology in this context the higher level geometrical design of a learning ...
10
votes
1answer
823 views

Are information processing rules from gestalt psychology still used in computer vision today?

Decades ago there were and are books in machine vision, which by implementing various information processing rules from gestalt psychology, got impressive results with little code or special hardware ...
9
votes
0answers
58 views

Will parameter sweeping on one split of data followed by cross validation discover the right hyperparameters?

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 ...
9
votes
1answer
195 views

Deep Networks and generalisation of Hopfield Networks

Hopfield Nets are able to store a vector and retrieve it starting from a noisy version of it. They do so setting weights in order to minimise the energy function when all neurons are set equal the ...
9
votes
5answers
306 views

Can an AI be trained to generate the outline of a story?

I know that one of the recent fads right now is to train a neural network to generate screenplays and new episodes of e.g. the Friends or The Simpsons, and that's fine: it's interesting and might be ...
8
votes
5answers
4k views

Which machine learning algorithm can be used for pattern recognition?

I need a machine learning algorithm to identify any patterns in a CSV file, which contains details of a cache performance of a CPU workload. More specifically, the CSV file contains columns like ...
7
votes
0answers
78 views

Will quantum computing have any kind of effect on the development of AI?

Recently, according to some reports Google achieved something called 'Quantum Supremacy'. Whether its true or not remains to be seen. But my question is does Quantum Computers or the principle they ...
7
votes
1answer
84 views

How does Atlas from Boston Dynamics have human-like movement?

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 ...
7
votes
1answer
437 views

Loss function for Hierarchical Multi-label classification

I am looking to try different loss functions for a hierarchical multi-label classification problem. So far, I have been training different models or submodels like multilayer perceptron ( MLP )branch ...
7
votes
3answers
245 views

Can some one help me understand this paragraph from Nvidia's progressive gan paper?

Furthermore, we observe that mode collapses traditionally plaguing GANs tend to happen very quickly, over the course of a dozen minibatches. Commonly they start when the discriminator overshoots, ...
6
votes
2answers
545 views

How to create a good fitness function?

In genetic algorithms, a function called "fitness" (or "evaluation") function is used to determine the "fitness" of the chromosomes. Creating a good fitness function is one of the challenging tasks in ...
6
votes
2answers
96 views

Why are documents kept separated when training a text classifier?

Most of bibliography consider text classification as the classification of documents. When using bag of words and bayesian classification, they usually use the statistic TFIDF, where TF normalizes the ...
6
votes
0answers
241 views

Can we use the recursive least squares as a learning algorithm to an ADALINE?

I'm new to neural network, I study electrical engineering, and i just started working with ADALINEs. I use Matlab, and in their Documentation they cite : However, here the LMS (least mean squares) ...
6
votes
1answer
107 views

Synapses automatically select it's neurons

I know the basics of Artificial Neural Networks. For instance; make dot product with the weights and every neuron from previous layer. Adjust the weight by error. And done, That is how I see neural ...
6
votes
2answers
81 views

How much can the addition of new features improve the performance?

How much can the addition of new features improve the performance of the model during the optimization process? Let's say I have a total of 10 features. Suppose I start the optimisation process using ...
5
votes
1answer
37 views

Why do very deep non resnet architectures perform worse compared to shallower ones for the same iteration? Shouldn't they just train slower?

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 ...
5
votes
0answers
32 views

Question about minimizing sum of remainders

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=...
5
votes
0answers
21 views

What is the impact of using multiple BMUs for self-organizing maps?

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 ...
5
votes
1answer
79 views

How to detect frauds in advertising business using machine learning?

I am very beginner to this world. I still learning the basics of Machine learning and AI but i have a problem at hand and i am not sure which technique or Algorithm can be applied on it. I am working ...
5
votes
0answers
41 views

Choosing Machine Learning Algorithm: Learning-Based Testing

This is my first project using machine learning so I'm looking for some guidance. I am extending a model-based testing (MBT) system to a learning-based testing system by integrating a machine learning ...
5
votes
1answer
98 views

How do I compute the variance of the return of an evaluation policy using two behaviour policies?

Suppose there is an evaluation policy called $\pi_{e}$ and there are two behavior policies $\pi_{b1}$ and $\pi_{b2}$. I know that it is possible to estimate the return of policy $\pi_{e}$ through ...
5
votes
2answers
119 views

Why do layered neural nets struggle with continous data?

In this article here, the writer claims that a new type of neural net is required to deal with data that is both continuous, and also sparsely sampled. It was my understanding that this was the ...
5
votes
1answer
190 views

Building AI from chess - data shape from simulation

Problem My problem is the following: Given 1000 wins, losses, and ties from a chess simulation I am using, what shape should each game be (I.e., sequence of moves leading to win/loss/tie) in order to ...
5
votes
2answers
384 views

Reinforcement Learning with asynchronous feedback

I want suggestions on literature on Reinforcement Learning algorithms that perform well with asynchronous feedback from the environment. What I mean by asynchronous ...
5
votes
2answers
69 views

Two data classes for a convolutional neural network, can one have a LOT more images for training than the other?

I have two classes in the training set: one that has images with a feature and the other of images without that feature. Can there be a LOT more images with "no feature" so I can fit in all possible ...
5
votes
0answers
122 views

How to design 4D Deep Recurrent Neural Networks using Tensorflow?

I want to design a simple model that predicts the movement of coordinates with RNNs. In a typical three-dimensional LSTM model, one feature is encoded as one hot encoding, and the ...
5
votes
1answer
111 views

Using ConceptNet5 to find similar systems to solve specific problems?

I installed a local running instance of the ConceptNet5 knowledgebase in an elasticsearch server. I used this data to implement the so-called "Analogietechnik" (a creativity technique to solve a ...
5
votes
1answer
52 views

Which marketing-related classification challenges is a feed forward neural network suited to solve?

I am trying to think of some marketing-related classification challenges that a feed-forward neural network would be suited for. Any ideas?
5
votes
2answers
88 views

What is the tolerance level of Standard-deviation of ANNs accuracy?

Just working with fully connected NNs (supervised learning), I found that models trained for, say NLP, on identical data sets with identical parameters to algorithms; but at different times, can ...
5
votes
3answers
182 views

What are the algebraic properties of intelligence?

Some have said, "Two heads are better than one." That's true if they are collaborating. If not, the two together may be worse than zero. Although that's a rhetorical opening paragraph, this is a ...
4
votes
1answer
30 views

dimensions of hidden layer and cell state layer in LSTM

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 ...
4
votes
1answer
43 views

How to deal with large (or NaN) neural network's weights?

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 ...
4
votes
0answers
34 views

Transformer: Position-wise Feed-Forward network

The Transformer model introduced in "Attention is all you need" by Vaswani et al. incorporates a so-called position-wise feed-forward network (FFN): In addition to attention sub-layers, each of the ...
4
votes
1answer
43 views

How does the network know which objects to track in the paper “Label-Free Supervision of Neural Networks with Physics and Domain Knowledge”?

I was reading the paper Label-Free Supervision of Neural Networks with Physics and Domain Knowledge, published at AAAI 2017, which won the best paper award. I understand the math and it makes sense. ...
4
votes
0answers
29 views

Get the position of an object, out of an image

I have some images with a fixed background and a single object on them which is placed, in each image, at a different position on that background. I want to find a way to extract, in an unsupervised ...
4
votes
1answer
63 views

How do we determine whether a heuristic is better than another?

I am trying to solve a Maze puzzle using the A* algorithm. I am trying to analyze the algorithm based on different applicable heuristics. Currently, I explored the Manhattan and Euclidean distances. ...
4
votes
0answers
22 views

Extending FaceNet’s triplet loss to object recognition

FaceNet uses a novel loss metric (triplet loss) to train a model to output embeddings (128-D from the paper) such that any two faces of the same identity will have a small Euclidean distance, and such ...
4
votes
1answer
74 views

An intuitive explanation of Adagrad, its purpose and its formula

It (Adagrad) adapts the learning rate to the parameters, performing smaller updates (i.e. low learning rates) for parameters associated with frequently occurring features, and larger updates (i.e. ...
4
votes
1answer
80 views

What is the difference between graph convolution in the spatial vs spectral domain?

I've been reading different papers regarding graph convolution and it seems that they come into two flavors: spatial and spectral. From what I can see the main difference between the two approaches is ...
4
votes
0answers
19 views

Video summarization similar to Summe's TextRank

We have the popular TextRank API which given a text, ranks keywords and can apply summarization given a predefined text length. I am wondering if there is a similar tool for video summarization. ...
4
votes
2answers
72 views

MCTS for non-deterministic games with very high branching factor for chance nodes

I'm trying to use a Monte Carlo Tree Search for a non-determinstic game. Apparently one of the standard approaches is to model non-determinism using chance nodes. The problem for this game is that it ...
4
votes
0answers
81 views

What is the difference between GAT and GaAN?

I was looking at two papers Graph Attention Networks (GAT) by Petar Veličković and GaAN: Gated Attention Networks for Learning on Large and Spatiotemporal Graphs by Jiani Zhang. I'm trying to ...
4
votes
0answers
77 views

Catastrophic Forgetting on Pong Environment using DQN

I am running a basic DQN on the Pong environment. Not a CNN, just a 3 layer linear neural net with ReLUs. It seems to work for the most part, but at some point my model suffers from catastrophic ...
4
votes
0answers
46 views

A* is similar to Dijkstra with reduced cost

If the heuristic $h$ satisfies the additional condition $h(x) ≤ d(x, y) + h(y)$ for every edge $(x, y)$ of the graph (where d denotes the length of that edge), then $h$ is called monotone, or ...
4
votes
1answer
60 views

Psychological models at Facebook et al

As a layman in AI I want to get an idea how big data players like Facebook model individuals (of which they have so many data). There are two scenarios I can imagine: Neural networks build clusters ...
4
votes
0answers
168 views

How to implement a neural network for Flappy Bird in Python?

I am new in the field of AI. I am working to create the flappy bird using Genetic Algorithm. After reading and seeing some examples, I saw that most implementations use a Neural Network + Genetic ...
4
votes
1answer
70 views

AI method for evaluating user performance based on audio pitch re: public speaking

First I will clarify the context, I have to learn new technologies for my bachelor thesis. I am making a mobile application similar to Flappy Bird, except it's voice controlled. The idea is to have ...
4
votes
1answer
64 views

How to deal with small amount of labeled samples?

I'm trying to develop skill to deal with very small amount of labeled samples (250 labeled/20000 total, 200 features) practicing on Kaggle "Don't Overfit" dataset (Traget_Practice have provided all 20,...
4
votes
1answer
125 views

What's the advantage of log_softmax over softmax?

Previously I have learned that the softmax as the output layer coupled with the log-likelihood cost function (the same as the ...
4
votes
0answers
50 views

Inconsistent definitions of the retrace

In Section 4.3 of paper Learning by Playing - Solving Sparse Reward Tasks from Scratch, the authors define Retrace as $$ Q^{ret}=\sum_{j=i}^\infty\left(\gamma^{j-i}\prod_{k=i}^jc_k\right)[r(s_j,a_j)+\...

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