Questions tagged [artificial-intelligence]

Artificial Intelligence (AI) is a topic in computer science that deals with the study / creation of intelligent machines. Use this tag for on-topic questions that have an AI aspect.

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Bayesian Q-learning

Suppose that, for every state $s$, there is a set of actions $\mathcal{A}(s)$ that can be chosen in that state. Let $Q(s, a)$ denote the expected utility of choosing action $a \in \mathcal{A}(s)$ in ...
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335 views

Interpreting hidden layer representations in ANNs

I'm using the fann library for writing an Artificial Neural Network in C++. I trained my network for the task of recognizing faces inside a set of 128x128 .png images, using three different algorithms:...
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875 views

Why is the derivative of the LSTM cell state w.r.t. to the previous cell state equal to the forget gate?

I keep seeing this online, on Quora and Machine Learning subreddits but I don't get it. Here's some basic math to show otherwise: We use this equation for the cell state: $c_t = f_t \odot c_t\__1 + ...
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518 views

How does a maze game / directed paths map to a Neural Network?

I am trying to understand how a maze game's possible paths and possible moves are mapped out in a Neural Network. Let's take this example here: http://cdn.intechopen.com/pdfs-wm/10916.pdf Agent can ...
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1answer
23 views

Dynamic interactive learning

I am trying to solve a classification problem where I have a set of known X values. I know the classification objective i.e. the discrete set of values the Y can take. However, I don't have any ...
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65 views

Find Feature Weighting in Deep Learning

If I train a deep neural network on standard tabular data (csv file etc. with labeled features) is there a good way to gauge how important each feature is in a particular new instance's prediction ...
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1k views

Algorithm to detect time series anomalies (outliers) (using Apache Spark)

I am currently new to machine learning and I will be working on a project that involves using a Machine Learning library to detect and alert about possible anomalies. I will be using Apache Spark and ...
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20 views

How does one solve the premise selection problem with imitation learning?

I was reading the following two new papers (HOList, Graph Representations) applying Machine Learning to Theorem Proving in Higher Order Logic. The main thing that I am unsure about is the following ...
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23 views

Transfer Learning in domains other than Image processing and NLP

Can Transfer Learning be applied in domains other than Image processing or NLP? I am trying to apply it on clickstream data (for propensity modeling). Any reference would be greatly appreciated.
2
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1answer
144 views

What is the difference between Generative Adversarial Networks (GAN) and Generative Antagonistic System (GAS)?

What is the difference between Generative Adversarial Networks (GAN) and Generative Antagonistic System (GAS) in the neural network?
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282 views

When to use batch normalization in a Fully Convolutional Network

I understand what batch normalization does but I'm not sure at what point it becomes overkill. With regards to a U-net, based on just the rough definition that batch normalization normalizes the ...
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43 views

Neural Networks for predicting Energy at particular date

I am trying to predict Solar Energy value at particular date.So,for this I am applying Artificial Neural Networks model.I am having problem in deciding activation function. Since sigmoid function ...
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145 views

Understanding the second hidden layers of convnets

Having studied ordinary fully connected ANNs, I am starting to study convnets. I am struggling to understand how hidden layers connect. I do understand how the input matrix forward feeds a smaller ...
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356 views

Random Forest regression model in R and data overfitting

I have trained my random forest model on a 74,000 training examples where each example consists of two proteins Amino Acids sequence (20 characters) and some numeric values representing the similarity ...
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41 views

Deductive reasoning and artificial intelligence

AI has proven to be extraordinary effective for solving certain types of intellectual problems that we thought before only our brains could solve. The number of applications is tremendous: engineering,...
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14 views

Mathematical proof of tradeoff between estimation error and computation cost in mini-batch gradient descent

" with more examples, the estimate would have a lower standard error, but the return is less than linear compared to the computational burden we incur." Came across this line while studying one ...
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13 views

Is it possible to reverse-engineer a variable which has a moderation effect in a multiple regression, given the other variables?

I am interested in simulating a hypothetical variable Z which moderates the relationship between X (predictor) and Y (outcome variable), while controlling for C (covariate). All variables are ...
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1answer
58 views

SVM in the classification layer of a Feedforward neural network

I want to use SVM in the classification layer of a 2 layer feedforward neural network. Need guidance from the community on how to approach this problem. This involves capturing the features from the ...
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287 views

How to handle missing data in PPCA

I am implementing a paper "Probabilistic Principal Component Analysis" (PPCA) which deals with a dataset where each vector suffers from at least one missing value missing values. Generally, PPCA ...
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196 views

Proof of NOT initialization of weights to zero

Can anyone provide me the mathematical details to why we shouldn't initialize a neural network (single layer ANN) weights to zero? In multi-layer we don't initialize it to zero because of loss of ...
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30 views

Policy space optimization? Reinforcement learning

What are the reasons that you have an easier time choosing a Policy optimization algorithm when the state space is high dimensional, are there also any other reasons in the task's attributes for ...
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37 views

Is reseating passengers a reinforcement learning problem?

Requirement is to optimally move passengers from one seat map to another which has a different configuration. Move should be based on many rules like - 1) Families should be sitting together 2) Those ...
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0answers
517 views

Understanding Proximal Policy Optimization

I'm a beginner in Reinforcement Learning, and have been learning about Policy Optimization methods like Proximal Policy Optimization and Trust Region Policy Optimization. I had a couple questions ...
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78 views

Quiz master agent using reinforcement learning

I am working on developing a quiz master agent using reinforcement learning. Please verify my approach and provide feedback. Also, please suggest which reinforcement learning methods are suitable to ...
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0answers
166 views

Adaptive (automated model selection) algo for simple time series models in Python?

I'm looking to create a predictive model for time series data using historical data only (no other variables) and simple curve fits (linear, polynomial, exponential etc). The issue is that I'm trying ...
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54 views

Applicability of using Back-Propagation Neural Network given continuous class labels

I am given a dataset where the class labels are continuous values between [-1,1]. Based on this, I have few questions: Can I use Back-Propagation Neural Network (...
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111 views

What's Libratus made of?

I'm trying to understand how Libratus is working. I found that there were 3 main parts, one using counterfactual regret minimization to learn to play from scratch. an end-game solver as well as ...
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233 views

Oblique random forest with ridge,svm, pls are resulting lesser accuracy than random forests

I am having 20 features with both discrete values and continuous values attributes. I am trying to compare the performance of random forest and oblique random forest. ORF usually performs better than ...
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69 views

Machine Learning: Is exploring learning rate manually still necessary with an exponential decaying learning rate?

If we have an initial learning rate high enough and a suitable decay factor for exponentially decaying the learning rate over a certain number of epoch, is it still need for us to manually explore the ...
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1k views

Architecture of the Triplet Neural Network

I want to implement face recognition neural network like in this topic(Step 3: Encoding Faces) using dlib library. I already conducted a some research and found out that it's triplet neural network ...
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1answer
65 views

Can you know in advance whether machine learning is going to work for a problem?

Machine learning is in fashion these days in many industries. So business folks think it can be applied to anything to make things great again. My experience tells me that there are problems where it ...
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2answers
65 views

How do I cluster/group people together given their durations for an given event?

I am new to machine learning and do have a very large dataset for a set of 100 people over a period of 1 year. and the goal is to find out who are buddys based on their lunch times. I have the ...
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78 views

Alternatives to Job Sequencing using Optimization

I have to N jobs to be assigned in a sequence to a Machine/User. I know using optimization technique we can find an optimal sequence. But in my case there are lot of parameters (some to be minimized (...
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84 views

Which ML algorithm is suitable for the following problem?

Assume i have x states each defined by an n-dimensional feature vector. In addition i have a set of actions which can be taken in each state resulting in a state action score. What would be an ...
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1answer
98 views

Limit multiclassification SVM - ANN

I have some questions on the limits of SVM and ANN for multiclass problem. I know about "one vs all" and "all vs all" strategies but I only want to know the limit of a unique SVM and ANN. Is there a ...
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1answer
531 views

How to build a machine learning system (smart system) that updates automatically?

I've been doing machine learning. I have done lots of learning related to data analysis and ML algorithms, and I've got very good results and I understand the algorithms. However, my approaches are ...
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2answers
59 views

Big categorical data

I am trying to predict the price of used vehicles using three different models: Regression, ANN, and random forest. I am having 6 variables as an input for my model. One of my variables is the ...
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11 views

How is the length of the output for encoder-decoder (seq2seq) models determined

I am trying to understand how encoder-decoder models works. The encoder receives a sequence and the length is known. However the output of the encoder is just a single word vector capturing the ...
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1answer
30 views

Correlation between features and the target

I am working on an AI project to predict the life time of an industrial tool. the data I have represents the consecutive Power values of the spindle during each use of the tool to produce a new piece. ...
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0answers
10 views

What does non parametric instance separation mean in this paper abstract?

I was reading the abstract of this paper - https://arxiv.org/pdf/1903.12355.pdf where they mention this paragraph in their abstract Unsupervised approaches to learning in neural networks are of ...
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17 views

Implementing Actor-Critic with Experience Replay for Continuous Action Spaces

I have been trying to implement the ACER algorithm for continuous action spaces in reinforcement learning. The paper for the algorithm can be found here: Sample Efficient Actor-Critic with Experience ...
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1answer
24 views

How can I draw decision boundaries for three different classes in Logistic Regression?

I understand the equation to draw a decision boundary in Logistic Regression with 2 independent variables and 2 different classes but when it comes to 3 different classes with 2 different independent ...
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42 views

Why Expectation and Maximization algorithm not used in Machine Learning while Gradient Descent algorithm used in Machine Learning?

I know that Newton Raphson, Expectation & Maximization, and Gradient Descent are all known to be optimization methods. Somehow, I wonder why Gradient Descent is chosen to be used in most of ...
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28 views

In feature selection, what the size of the data set is considered as too small? Is this an appropriate use of machine learning?

I am in a non-computer science field, and machine learning is being blatantly misused in my field. I recently got a journal paper to review, where the researchers used machine learning to develop a ...
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8 views

Can the same individual from a population be chosen in a genetic algorithm?

One population contains 10 individuals, from these 10, 8 are picked based on a selection mechanism. Let's say they are picked using the rank based selection mechanism (so the best ranked has a higher ...
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19 views

Text Match for Description Fields

I have a long file with the list of item id's and their descriptions. These descriptions are like "The Brawn White Bolt Laser 10W" and "Laser for 10 Watt White Bolt" with different item id's. Though ...
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1answer
34 views

What does State of Art Result means in context of ML/DL

Wondering what it means to have a state of art result.Is it a relative term or a standard? For Exmaple: If I have developed 2 models one with higher accuracy can i say i have achieved state of art ...
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21 views

Training a multi-layer perceptron (MLP) with a modified basis function

Consider a simple 3-layer MLP such as this. Each hidden layer implements y=xw+b where y is the output activation matrix of the ...
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19 views

How to understand 4 steps of Monte Carlo tree search?

From many blogs and this one https://web.archive.org/web/20160308070346/http://mcts.ai/about/index.html We know that the process of MCTS algorithm has 4 steps. Selection: Starting at root node R,...
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33 views

Is there a model or algorithm to improve digital drawings?

given a bad drawing, the algorithm should deform the edges of the bad drawing and fill them with color so that it looks more like a learned character. the entry would be a very poorly made drawing of ...