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

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Classification problem where one attribute is a vector

Hello I am a layman trying to analyze game data from League of Legends, specifically looking at predicting the win rate for a given champion given an item build. Outline A player can own up to 6 ...
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1answer
29 views

While using K-means, how do I represent IP addresses and languages on the coordinate axis?

I'm using K-means for unsupervised learning, using data vectors with an IP address and a language. I need to represent them in an abstract way, so that I can use this algorithm.
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1answer
17 views

Should activation function be monotonic in neural networks?

A lot of activation functions in neural networks (sigmoid, tanh, softmax) are monotonic, continuous and differentiable (except of may be a couple of points, where derivative does not exist). I ...
3
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0answers
51 views

The runtime of a neural net with given numbers of observations, features, and neurons

If I have $n$ training observations, $m$ number of features per observation, and my neural network has $x$ neurons in the 1st layer, $y$ neurons in the 2nd layer, and 1 output neuron, what is the ...
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0answers
36 views

Featurizing images of different dimensions

I'm building a non linear svm for images to solve a classification problem with domain {0, 1} and I'm currently doing featurization. What I want to do is create 3 features for each pixel representing ...
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2answers
92 views

Train Neural network with infinite amount of data [closed]

Does a sufficiently complex neural network guarantee to find the optimal solution, given an infinite amount of data and the back propagation technique for training? In other words, given an infinite ...
3
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0answers
55 views

What is the simplest written language to work on in handwriting recognition?

Handwriting recognition is an important but very complicated domain of Computer Sciences. Computers nowadays do a quite fair job even if there is room for improvement in the future. I am wondering if ...
2
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1answer
35 views

Inferring Social Ties

In some papers, they proposed a model in which the joint posterior probability was modeled as[1]: $$ P(Y|\textbf{X},G) = \frac{P(\textbf{X},G|Y)P(Y)}{P(X,G)} \propto P(\textbf{X}|Y) \cdot P(Y|G)$$ ...
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2answers
308 views

Google's Deep Dreamer

I was just wondering on a more technical side, if anyone could explain what Google does to create these amazing images from it's deep dream system. Could anyone explain to me in a step by step way, ...
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0answers
30 views

How can neural networks learn to create new things (sentences for example)? [closed]

I have already taken a college course at my uni on machine learning where we implemented all the basic ML programs: linear regression, logistic regression, basic neural network with logistic ...
3
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1answer
21 views

Learning a small disjunction using an input distribution of our choice

I have a boolean function $f: \{0,1\}^n \to \{0,1\}$ that I know takes the form $$f(x_1,\dots,x_n) = x_{i_1} \lor x_{i_2} \lor \dots \lor x_{i_k}.$$ I don't know the values of $i_1,\dots,i_k$, but I ...
2
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1answer
19 views

Learning a small disjunction

I have a boolean function $f: \{0,1\}^n \to \{0,1\}$ that I know takes the form $$f(x_1,\dots,x_n) = x_{i_1} \lor x_{i_2} \lor \dots \lor x_{i_k},$$ but I don't know the values of $i_1,\dots,i_k$. ...
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0answers
41 views

What is the activation function, label and loss function for Hierachical Softmax

Several papers(1 (originator), 2, 3) suggest the use of Hierachical Softmax instead of softmax for classification where the number of classes is large (eg many thousand). I haven't been able to get ...
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1answer
46 views

How to identify and find navels from human pics

I have a specific question and not sure what tools I can use to finish my projects. I know this may has been well solved, but I am quite new to the image recognition and detection area and don't know ...
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2answers
88 views

Machine learning algorithm(s) for recognizing simple graph patterns

I generate some simple graphs based on usage stats of a website, and they may look like these: I call the 'pattern' on the left 'convergence', and the 'pattern' on the right 'divergence'. The ...
6
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1answer
41 views

Conflict Driven Clause Learning backtracking clarification

On the wikipedia page here it describes pretty well the CDCL algorithm (and it seems the pictures were taken from slides created by Sharad Malik at Princeton). However when describing how to backtrack ...
3
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0answers
63 views

Unsupervised Learning: BCM or Oja's Rule

I am learning about unsupervised machine learning, and am a bit confused regarding different algorithms to update weights. So, I understand that both Oja's Rule and BCM can be used. In Oja's rule: ...
2
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2answers
56 views

Huffman tree generation if the frequency is same for all words

Can a valid Huffman tree be generated if the frequency of words is same for all of them? Example : ...
2
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0answers
9 views

What is the meaning of the output weights of a Conditional Random Field (CRF) model?

Problem When train my linear chain CRF with annotated observations, I feed it with a number of sequences containing observation values and a "ground-truth" label for each observation. I'm currently ...
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1answer
53 views

Standard problem sets for metaheuristics

I'm wanting to dabble with metaheuristics and am interested to know what the "hello world" problem sets are. In other words, what are the common problems (e.g Traveling Salesman, Vehicle Routing ...
0
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1answer
51 views

How to use frame based speech features for learning using a neural network classifier?

I am doing supervised learning on speech audio files using neural networks. For this purpose, I'll have to extract features from the audio file. But since an audio file is a time varying signal, it is ...
0
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1answer
36 views

A clarification on the taxonomy of Evolutionary Algorithms

A rather basic question but I am confused about the characterization of a certain local search method which I want to describe in the framework of EAs. In particular, consider an EA which in every ...
3
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1answer
57 views

Choice of machine learning algorithms frequency of parts of speech

I'm new to machine learning. I have text, and I tag the text according to their parts of speech tag ie walk is tagged as verb, etc. I tag entire sentences, and then convert them into a vector based on ...
7
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1answer
38 views

PAC learning model definition

The probably approximately correct (PAC) learning model is defined as: A concept class $C$ is said to be PAC-learnable if there exists an algorithm $A$ and a polynomial function $poly(·,·,·,·)$ such ...
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0answers
37 views

An example for a finite hypothesis class which is not PAC learnable?

I know that with a bounded loss function, every finite hypothesis class is PAC learnable. Are there examples for non PAC learnable hypothesis classes with an unbounded loss function?
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23 views

Optimal Design of Cascaded Classifier

Consider a cascade of classifiers and a binary classification task. Cascade consists of some number of strong classifiers (n) each of which consists of some number of weak classifiers (m_i, where i = ...
3
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1answer
38 views

MAP estimation (for stationary iid gaussian environment)

This is my first post, and have been self studying Haykin's Neural Networks and Learning Machines book. I'm not sure if this is a typo or if I'm doing something wrong, but I've been stuck on a ...
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0answers
9 views

Finding the minimal set of n-tuple instances for a training set, to be used in Candidate-Elimination algorithm

The Candidate-Elimination algorithm(which may go by another name), is an algorithm which received a set of instances for input and outputs a General and Specific hypothesis. The algorithm can be seen ...
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1answer
39 views

Online supervised learning algorithm

I have labeled examples coming in on the fly, thus I need to create a classifier from sequential data instead of a static example set. Incoming data is fully labeled, there are no unlabeled examples. ...
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0answers
153 views

some kernel and greater margin, how this occures?

I read following notes, and couldn't get it. any idea or hint would highly appreciated. a SVM classifier using a second order polynomial kernel. The first polynomial kernel maps each input data x to ...
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2answers
60 views

Different weight sets for same problem?

Considering the case that we have a fixed set of training examples and a fixed ANN (i.e same number of input,output and intermediate layers). Is it possible that there exists more than one set of ...
0
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1answer
36 views

Kernel Perceptron vs Polynomial Perceptron

I was looking at Support Vector machines (SVM) kernels. Looking at Polynomial Kernel and Kernel Perceptron I was curious how they differ? Work Done Polynomial Kernel: ...
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0answers
23 views

Any good algorithms for 3d volume alignment by feature extraction, especially ones involve machine learning?

I am trying to align 3d mri brain images of different rat individuals. I have dozens of examples that have been aligned manually, which are good resources for machine learning. I am considering ...
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1answer
43 views

Transformation from one feature space to another

I have found the following example: As an example consider the case when the input space $ {\mathcal{X}}$ consists of images of $ 16\times 16$ pixels, i.e. $ 256$ dimensional vectors, and we ...
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0answers
20 views

Learning a regex from string examples? [duplicate]

Given some strings, is there some algorithm (and program that implement such an algorithm) that can create a regex which matches some of the given strings and not the other given strings? Note that ...
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1answer
34 views

Collecting data(images) using a crawler [closed]

Please let me know, if this goes here, if not, please point out where I should post this. Thanks in advance. So I require huge number of training data, mostly images. This is a pet project, only for ...
4
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1answer
77 views

PCA and Eigenvectors

I am trying to understand how PCA works, and think I got most of it except... By calculating eigenvalues/vectors of the covariance matrix of the original dataset allows to find those dimensions where ...
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1answer
45 views

Classification when some classes are dependent

I think my problem can easier be explained via an example: Assume we have a dataset containing the images of 10 different mammals, let's say lion, elephant, cat, ... and horse. We have a 20-class ...
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0answers
26 views

Research work on computational models for a “specific” person's behaviors

Is there active research work on creating computational models of a "specific" person's behaviors (general behaviors, emotions, actions...)? What are some references for such research? I tried google ...
0
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1answer
35 views

Text features in decision tree

Right now I am doing some problems on application of decision tree/random forest. I am trying to fit a problem which has numbers as well as strings (such as country name) as features. Now the library, ...
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0answers
72 views

Maximum likelihood estimate for softmax function

Given an undirected graphical model with no edges and only N nodes, I am trying to find a closed form solution to the ML estimate of each node given that $p(x|\theta)=\frac{\exp(\sum_{s\in ...
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0answers
20 views

DAG that can capture any joint distribution

I am trying to do the following question: draw a directed acylic graphical model on five variables which can capture any joint distribution. I'm not sure I understand what it means by "can capture any ...
7
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2answers
105 views

PAC learning axis parallel rectangles

I am trying to understand the proof that the axis parallel rectangles are PAC learnable in the realizable case. This means that given $\epsilon, \delta$ with enough data we can find a function $h$ ...
3
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1answer
39 views

What does does $O$ mean in this context?

I understand big O notation in computational complexity theory, but I don't see how it applies in the equation below. From Pattern Recognition and Machine Learning: If we weren't familiar with ...
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1answer
85 views

Bayes net: algorithm to calculate joint distribution?

I recently started studying bayesian networks and I am now implementing an exact inference algorithm: enumeration. I am aware of the complexity and inefficiency of this method but I want to fully ...
2
votes
1answer
56 views

What is an edge hop?

I've tried googling it, but found nothing. Here is the context it's in: From Bayesian Reasoning and Machine Learning: Adjacency matrices may seem wasteful since many of the entries are zero. ...
2
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2answers
64 views

What happens when you don't use a metric in k-means?

K-means is a clustering algorithm which works like this: ...
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0answers
53 views

Hessian-Free instead of LSTM for Recurrent Net Machine Translation

Last year, Ilya Sutskever and collaborators came out with a paper about a recurrent LSTM net that learns sequence to sequence mappings for machine translation. It's somewhat surprising that the ...
0
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1answer
102 views

Build Automatic Speech Recognition (ASR) from scratch [closed]

I want to build a Automatic Speech Recognition (ASR) engine for myself, but I've no idea from where to start. I've read that most ASR's are build upon Hidden Markov Models, but also I've read that ...
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0answers
22 views

Amplifying a Locality Sensitive Hash

I'm trying to build a cosine locality sensitive hash so I can find candidate similar pairs of items without having to compare every possible pair. I have it basically working, but most of the pairs in ...