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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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6 views

Best arm identification (multi armed bandits)

Can anyone explain the proof of theorem 8 in paper. "Action Elimination and Stopping Conditions for the Multi-Armed Bandit and Reinforcement Learning Problems".
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0answers
11 views

Augmanted Reality [on hold]

I want to know The Technology of AR and The Tools i should have to build a AR Reality App https://en.wikipedia.org/wiki/Augmented_reality#Hardware
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18 views

Dimensionality Reduction to Find Abstract Concepts

I have a list of say 1000 topics and each are related to computer programming field such as if/else topic, while loop , for loop, integers, strings ect. I want to create a concept map for them which ...
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1answer
20 views

Checking if a kernel is valid

The kernel is $K(x,z) = \sum_{i=1}^D (x_i+z_i)$ My approach was trying to express $K = \phi(x)^T\phi(z) = (x_1 x_2 ... x_D \quad 1 1 ...1)(1 1 ...1\quad z_1 z_2 ... z_D )^T$ where $\phi$ is 2Dx1 ...
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0answers
31 views

What is the quantity sold for a specific fruit & country combination?

What is the algorithm that generates these potential quantities that meet the given criteria? Essentially - there are number of quantities for a fruit and country combination. E.g: ...
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0answers
9 views

Principle Component Analysis Help

My Attempt Part A: 1 dimension, and 2 dimensions for the PCs. Part B: Number of stations. Part C: not sure...
2
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1answer
32 views

Is Artificial General Intelligence possible with our current machine learning models? [closed]

In other words, is artificial human level intelligence not possible yet just because of limitations in processing power and amount of data required to train the models? Or we don't have the knowledge ...
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0answers
11 views

how many hidden layers in an n-layer neural network

Simple terminology question: (should be easy to answer) How many hidden layers does an n-layer neural network have? I believe the answer is n-1. For example a single layer perceptron has no hidden ...
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0answers
14 views

Applications of signed permutations to machine learning

Are there some applications of signed permutations to machine learning? I searched on google and only found one paper. Thank you very much.
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19 views

Random Forest: Differentiable or non-Differentiable Classifier?

I have read on a web site that differentiability is an important property for Machine Learning. Its link is: https://www.quora.com/Why-%E2%80%98differentiable%E2%80%99-is-the-most-important-keyword-in-...
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0answers
15 views

No free lunch theorem and finite hypothesis class contradiction?

I am currently learning machine learning thanks to this course : https://webdav.tuebingen.mpg.de/is-class-2/Lecture4.pdf I know that a finite hypothesis class $H$ is PAC-learnable. Let's say I take a ...
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0answers
27 views

Candidate Elimination Algorithm - Simple Problem

I'm trying to understand version space learning and the Candidate Elimination algorithm. Define the set of most general and the set of most specific hypotheses. Take these training examples with the ...
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0answers
14 views

momentum term in back propagation

back propagation with momentum term means we update the weights like so: $\Delta w_{i,j}(n)= \eta*\delta_j(n)*y_i(n)+\alpha*\Delta w_{i,j}(n-1) $ what do we intialize $\Delta w_{i,j}(0)$ to?
3
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1answer
24 views

Why doesn't this derivation of the margin in a SVM give the correct result?

I'm trying to derive the optimization objective for an SVM (namely $1/\|w\|$), but I'm running into a little trouble. I've already read this question, which has certainly offered a lot of insight into ...
1
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1answer
18 views

The notion of PAC in approximation algorithms

In computational machine learning, the notion of Probably Approximately Correct means that (generally speaking) we can find (or "learn") with a high probability a function which has "low error". Is ...
0
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1answer
16 views

Choose the best classifier to predict the label of strings of a regular language

I have to tackle this problem: I have some strings that are my training set. These strings belong to a regular language corresponding to a deterministic finite automata (hidden namely I don't now it, ...
0
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0answers
16 views

FastText how it works?

So my question is how Supervised FastText works for the most part. I understood in the original paper they use bag of n-grams for features, but then they released a paper with enriching the word ...
2
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1answer
59 views

Mathematical proof for why gradient descent algorithm always converges

I am currently learning machine learning and I stumbled across gradient descent. I understand why the algorithm always converges to the global/local minimum when the learning rate is small enough in ...
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0answers
19 views

What are good examples of computational theories for A.I. according to David Marr's Definition?

I was reading David Marr's "Artificial Intelligence-A Personal View" and he talks about "computational theory of AI" or what he laters labels as "Type 1" Theory. He provides the example of Chomsky's ...
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2answers
111 views

Does deep learning infer P = NP?

The question comes from the following scenario, assume we have the traveler problem which is NP (the one where a traveler wants to visit all countries with the lowest cost(by summing up all flights)) ...
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2answers
40 views

What is the “spatial information” in convolutional neural network

deep learning research papers always claim that deeper layers of CNN have good "semantic information" but poor "spatial information". What is the spatial information exactly. Is that some activations ...
3
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0answers
25 views

How to compute the loss and backprop of word2vec skip-gram using hierarchical softmax?

So we are calculating the loss $$J(\theta) = -\frac{1}{T}\sum_{t=1}^T\sum_{-m \leq j \leq m} \log P(w_{t+j}|w_t;\theta)$$ and to do this we need to calculate $$P(o|c) = \frac{\exp(u_o^Tv_c)}{\sum \...
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1answer
50 views

VC dimension of finite unions of one-sided intervals

What is the VC dimension of $k$ finite unions of one-sided intervals: If we take 3 one-sided intervals like $(-\infty, a_1] $, $(-\infty, a_2] $ and $(-\infty, a_3] $, I think union of these ...
1
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1answer
59 views

Cost of computational representation in PAC-learning definition

I'm currently reading Foundations of Machine Learning by M. Mohri, A. Rostamizadeh, A. Talwalkar and according to their definition a concept class $C$ is said to be PAC-learnable if $$Pr_{S \sim D^m}[...
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0answers
24 views

How to get old top news? [closed]

I am not sure this is the right forum to ask. For a machine learning training, I need a dataset of old top news by keywords that can be organized by date. From where I can download it? I have seen ...
3
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1answer
39 views

(DROP) Data Reduction Algorithm - How it works?

I am studing a PHD framework which the propose is to reduce the dataset with the most representative samples for training a classifier. Maybe I am loosing something, but I could not undestand a ...
3
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1answer
31 views

Weird behaviour of softmax derivative?

I have been implementing some neural networks in MATLAB and recently I noticed a weird thing while implementing softmax derivative: Setting the derivative to one, rather than using the actual ...
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0answers
12 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 ...
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1answer
20 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 ...
3
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0answers
51 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
20 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
29 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
26 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
17 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
37 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
65 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
25 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 ...
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0answers
37 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 ...
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0answers
38 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
28 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 ...
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0answers
63 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
78 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 ...
2
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1answer
39 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
25 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
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1answer
23 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 $...
2
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1answer
59 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
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1answer
34 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
72 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 ...