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Questions about computer algorithms that automatically discover patterns in data and make good decisions based on them.

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0answers
20 views

Using CNN to learn the non-linear mapping between two images

I'm wondering if there a way to enable a CNN to learn the non-linear transfer between two images. For example, the original image looks like The target image looks like I would like to develop a CNN ...
0
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0answers
11 views

Can self-taught learning generalize to open-set classification?

Raina et al. introduced self-taught learning (essentially semi-supervised learning with unlabelled examples unrelated to the training set classes that we are trying to classify) to the ML community in ...
0
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1answer
18 views

How to calculate the weight between neurons in ANN?

I am currently learning Supervised ANN training using Backpropogation and I am stuck in this exercise. I calculated the δA using the equation at the bottom of the screenshot, however, I am unable to ...
4
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0answers
46 views

Why do AlphaGo and AlphaGo Zero include board history in the input features

Both AlphaGo and AlphaGo Zero include prior board states as input features (the "Turns Since" planes for AlphaGo, and the repeated 8-step history planes for AlphaGo Zero). What is the purpose of ...
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0answers
31 views

Should I gloss over the linear algebra chapter in the book “Deep Learning” by Ian Goodfellow? [closed]

Currently I am reading "Deep Learning" by Ian Goodfellow, Yoshua Bengio, and Aaron Courville. I'm on Chapter 2 which is the Linear Algebra section where they go over the linear algebra that pertains ...
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0answers
17 views

Defining an environment and States for a Reinforcement learning problem

I am new to the RL field and I am unable to understand the way the environment and states can be defined. I have referred a couple of videos and books, yet unclear. For example, if an environment ...
0
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1answer
11 views

Correct cost function of multi classification problem using neural network?

I am going through machine learning course on coursera. While going through the section on neural networks I came across the cost function for multi - classification problem using neural networks ( ...
3
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1answer
27 views

Why Don't We Use Non-ML Artificial Evolution?

I remember reading about Tom Ray's Tierra and how amazing the results it obtained were. However as far as I know, the only "evolution" based computer technology we use now is ML, which is very limited ...
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0answers
22 views

L1 sampling for sampling edges of a graph

I am trying to sample the edges of an undirected graph using weights. The goal is to run a sparsification algorithm on the graph. I see the point that L1 norm is best for sparsification. Can someone ...
0
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0answers
13 views

Implementing recurrent neural networks - matrix dimensions

This may be potentially better suited as a Linear Algebra question. I'm trying to implement the forward pass update rules for an LSTM unit. Following this definition: The problem is it is unclear ...
0
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1answer
15 views

Entry into Machine Learning and AI

Background: I haven’t done much programming and am currently in high school. I’ll be taking AP Comp Sci this coming year and have started learning Java recently. 4 related questions: 1. How much ...
3
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2answers
59 views

What is the State of The Art of Writer AIs (Deep Learning)?

Does anyone know if Deep Learning Bots can already, for example, train on many books of an author and output a similar but new book? I've been wanting to get into ML for quite a while but was ...
1
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1answer
24 views

Identify objects (bus) on the map based on coordinates (lat, lon)

Let's say I have an android app that frequently sends current GPS location of the user. If person is driving with bus, I can easily get GPS location of the bus and display it on the map and update it ...
1
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0answers
17 views

How can node2vec help find similar “roles” within a graph (nodes whose connections have similar structure within the graph)?

I have a question on the node2vec algorithm described in this paper. Node2vec is a deep learning algorithm that word2vec to graphs to learn embeddings. The authors claim that it can help find nodes ...
1
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0answers
33 views

Why don't Artificial Neural Networks Commonly Diverge?

Introduction: I'm using divergence here as to mean that the gradient is getting further and further from zero in stochastic gradient descent. I've written my own feed-forward neural network and tried ...
2
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0answers
24 views

Moon lander algorithm

Not talking about the actual moon lander, but an old game that was inspired by it (see screenshot). Suppose I wanted to write a program that "plays" this game: Can only operate the vertical thruster ...
0
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0answers
62 views

Machine learning for finding best fit?

How to apply machine learning method to learn to find a solution for the following problem, by going through multiple cases and learning from mistakes ? I am looking for an analytic solution for the ...
2
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1answer
38 views

Subsampling of Frequent Words in Word2Vec

I am reading through the following paper: https://papers.nips.cc/paper/5021-distributed-representations-of-words-and-phrases-and-their-compositionality.pdf Under section 2.3 on page 4 the authors ...
1
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1answer
35 views

The task of recognizing game units in the screenshot

I'm new to computer vision and I want to solve the task of recognizing the game units of the game Clash Royale in the screenshot. Briefly, there are about 70 different types of gaming units belonging ...
1
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1answer
21 views

Question on word probability for hierarchical softmax used in natural language processing

I am reading the following paper: https://papers.nips.cc/paper/5021-distributed-representations-of-words-and-phrases-and-their-compositionality.pdf On page 4 of the paper they describe the ...
1
vote
1answer
16 views

Parameter sharing / weight constraints in Neural Networks

I would like to train a neural network whose parameters (alternatively, weights) are subject to linear constraints such as $w_{i,j} = w_{i',j'}$, where $w_{i,j}$ denotes the weight from input node $...
1
vote
1answer
50 views

Is there a universal learning rate for NeuralNetworks?

I'm currently creating a NeuralNetwork with backpropagation/gradient descent. There is this hyperparameter introduced called "learning rate" (η). Which has to be chosen to guarantee not overshooting ...
2
votes
1answer
31 views

Using a 2nd neural network to predict 1st neural network prediction error

So for example, we are trying to predict the amount of rainfall in the afternoon base on continuous features such as humidity and temperature in the morning. 1st neural network: Regression neural ...
1
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2answers
69 views

The well-known classifiers that can be trained/tested in linear time [closed]

I am interested in collecting the list of the classifiers that (depending on their setting) can have linear time complexity (both in training and testing step) with respect to the number of samples $n$...
1
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1answer
13 views

Finding a non-boundary, local optimum of a non-convex function over a convex feasible region

I have a reasonably smooth non-convex non-monotone function in high(ish) dimensional space, that I wish to find a local minimizer for, over a convex feasible region (the intersection of a ball with a ...
0
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0answers
11 views

kernel function from polynomial basis functions

In chapter 3 & 6 of Bishop's Pattern Recognition and Machine Learning, he showed that the equivalent kernel based on eqn (3.62) and the standard kernel based on the feature space mapping eqn (6.10)...
0
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0answers
15 views

Clustering non-overlapping time series

I have thousands of times series of different length and different time. I want to group them together so that I know the optimal ones to pick as input for a ML algorithm and to document how they are ...
0
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0answers
13 views

Adding and removing output layer units of a neural network

I'm fairly new to deep learning, so if terminology makes no sense, please let me know so I can clarify what I mean. We're working with a neural network for applying classes to inputs. That is, each ...
1
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0answers
24 views

Clustering via Max-Cut

I wonder if there are papers that uses max cut algorithm(s) to cluster data. For example, if an edge between two nodes $u$ and $v$ indicate that $u$ and $v$ are different, then the max-cut in some ...
0
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1answer
32 views

Existence of Optimal Policy for infinite-state MDPs

It is well-know from Puterman's book (1994) that in any finite-state MDP, if there exists an optimal policy, then that policy is stationary and deterministic. How about MDPs with continuous state ...
1
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0answers
24 views

Multi Arm Bandit (MAB) — Increasing reward function

In the general stochastic MAB model, the reward obtained at each trial is generally assumed to be independent of previous trials and obtained from some fixed (but unknown) distribution. However, if ...
0
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0answers
11 views

VC Dimension of A Set of Hypothesis

I am confused about what does a VC dimension of a set of hypothesis means. I have two hypothesis, say $H_1$ with VC dimension of $x$, and $H_2$ of VC dimension of $y$. Does this automatically mean ...
2
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1answer
25 views

Capsule networks for classification with limited data

Capsule networks seem to match performance of convolutional neural networks on image classification tasks (more specifically on classification of handwritten digits in the MNIST dataset) 1. I have ...
0
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1answer
16 views

Naive Bayes' Classification and Using the Entire Vocabulary in the Denominator

I am working through the NLP notes for Naive Bayes' classification here: https://web.stanford.edu/~jurafsky/slp3/6.pdf Below $c$ is the class of the observation and $w_i$ is the $i$th word of a text ...
1
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1answer
14 views

CNN/Neural Network: Can I still estimate 3 parameters if my input data has insufficient parameter labels?

I am trying to simplify a CNN model. Currently, I need to train 3 different models (with the same architecture) to estimate each parameter. I am just wondering if there is a way to just train one ...
0
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0answers
17 views

Optimality of Bayes Classifier

I know this question has been asked a few times but I find it hard to understand the solutions. Say, here (For example, I don't understand why the true error is defined in that answer the way it is.) ...
2
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0answers
29 views

Approximate dot product between neural network output layer's parameter vector and input activations with winner-take-all hashing

In the paper Deep Networks with Large Output Spaces, Vijayanarasimhan et al. describe their approach to approximating the dot product between a neural network's output layer's parameter vector and ...
1
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0answers
12 views

How to use WISARD neural network to detect defects in banknotes

We learned about the WISARD neural network in my machine learning course. We said that for an $n\times k$ image, we would use discriminators having $n$ RAM neurons each of $2^k$ bits. The examples we ...
0
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0answers
34 views

stabilizing Q-Learning

I have this issue with Q-Learning that whenever I run it, it returns a different Q value for a certain state-action pair. Although, I am using decaying learning rate (e.g. 1/(time+1)) and gamma=0.99. ...
0
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0answers
10 views

integrate current field information for time series forecasting using RNN

I find an interesting question during my study and work, in time series modeling using RNN. It is a general time series forecasting problem, that suppose we have $R_t$ from $t=0,...,n-1$ and want to ...
4
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0answers
81 views

graph signal processing

What's the intuition behind a ''Graph fourier transform'' ? I'm not so much interested in mathematical details or technical applications. I'm trying to grasp what a graph fourier transform actually ...
0
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0answers
24 views

Q-Learning Error Bounds

I have searched a lot for this, but apparently there is no result on calculating any bound on the error $||Q-Q^*||$ when I stop Q-learning after say $N$ iterations ($Q$ is the vector of Q-values at ...
1
vote
1answer
26 views

Does selecting the same arm has the same reward?

In multi-armed bandit problem, we have a set of $K$ arms. In each round $t$, a bandit selects an arm $k$ and receives a reward $r_{kt}$. The objective is to maximize the rewards after $T$ rounds. My ...
1
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0answers
22 views

How would you go about creating a algorithm that should generate a shakespearean sonnet on any given theme

I need to create an algorithm that is going to create a shakespearean sonnet for a specific theme. This theme should be generated out of twitter tweets that have some hashtag. My current idea goes ...
1
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0answers
18 views

Attribute Selection for minimum number of clusters

I have a table consisting of some headers $P, Q, R, S$ (shown in blue in Table 1). According to the headers, the column $T$ is populated using some predefined logic. Now, any of the headers $P,Q,R,S$ ...
2
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0answers
41 views

Are there connections between the theory of computation and machine learning?

I am wondering if studying the Theory of Computation/ Computational Complexity theory, specifically Sipser's 'Introduction to the Theory of Computation' will help me do machine learning/statistics/...
0
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0answers
14 views

which machine learning technique use in this case?

I have came across a problem that the question is which machine learning technique to use. The case is the following: We have a set of persons that will be attending to a meeting, a person A has ...
0
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0answers
39 views

How to recognize digits in water meter image

I need to read the digits of images like the one below: From what I understand, this will involve: Registering and segmenting the image into each individual digit Hand labeling a bunch of these ...
0
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0answers
97 views

Use Machine Learning to predict when a Gas Station is running out of fuel

We have years of data on several Gas-Stations. Data about the Gas-Stations: the number of tanks, Gallons per tank, Location, number of pumps, kind of fuel, etc. Data on fuel consumption for x gas ...
0
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1answer
43 views

What does canonical extension mean?

Density-reachability is a canonical extension of direct density-reachability. What is meant by canonical extension? Source: A Density-Based Algorithm for Discovering Clusters in Large Spatial ...