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

learn more… | top users | synonyms

0
votes
0answers
12 views

What are Pairwise intensity comparison in binary image descriptors?

Recently many binary descriptors have come u like BRIEF, ORB etc. A common ste in such descriptors is to chose a sampling pattern and perform pairwise intensity comparisons for constructing the binary ...
-1
votes
0answers
32 views

Is there a vanishing gradient in RNN training? [on hold]

One of the often cited issues in recurrent neural network training is the vanishing gradient problem [1,2,3,4]. However, I came across several papers by Anton Maximilian Schaefer, Steffen Udluft and ...
2
votes
3answers
102 views

Does programming language detection need more input than natural language detection?

I wonder which one of the two needs a larger input to achieve a decent accuracy: programming language detection or natural language detection? More details: Definition of Language detection: ...
2
votes
1answer
26 views

Closed form solution for a single layer linear perceptron

Let f be a one-layer neural network which is linear (ie. no activation function). Let it have $p$ inputs and $q$ outputs. These are fully connected by weights $W$. We have $n$ inputs $x \in ...
0
votes
0answers
19 views

Clustering geo location coordinates (lat,long pairs) [closed]

What is the right approach and clustering algorithm for geo location clustering? Is it right to use Kmeans for location clustering, as it uses Euclidean distance and not Haversine formula as a ...
1
vote
0answers
15 views

Baseline approaches for likes prediction

I have a small user-item matrix (25k x 1.8k) describing how users liked or disliked some of the items. Users don't have any attributes but items have several features. I would like to be able to ...
2
votes
1answer
36 views

Generative Machine Learning algorithms on tree structure

I'm looking into PCFG sentence grammar dependency structure parsing using StanfordNLP PCFG parser. It generates tree structures represented as a string like this: ...
-1
votes
0answers
11 views

Which supervised ML is best for my scenario?

I have following data: ultra-sound audio recording, and I have the raw data of those samples, and of course the Fourier Transform data for those samples. Each dataset is assigned a value (for example ...
0
votes
0answers
45 views

Where to start studying about HTM?

I am looking for references (pedagogic and beginner friendly!) to these two topics, hierarchical temporal memory algorithms applied to deep planning problems (multi-layer) neural networks trained ...
1
vote
0answers
41 views

Two classes of documents. Find weighted relations between them

I have an NLP problem and a potential solution, but I’m a bit green here, so I’m looking for some validation or alternative suggestions. Background I have two types of documents: one is a set of ...
0
votes
0answers
21 views

Convergence of $Q$-learning

I have a intuitive question on the convergence of $Q$- learning. In $Q$ learning for each step a $Q$- value is learned for the state-action pair where the action is selected according to the ...
3
votes
1answer
41 views

Extracting features for texture classification

I m a beginner in the field of pattern recognition and computer vision. I m working on a project right now to classify t-shirt patterns into three categories i.e. solids, stripes and checks. I have ...
1
vote
0answers
22 views

What is the difference between “objective function”, “error function”, “criterion function” and “cost function” in the context of neural networks?

The title says it all: I have seen three functions so far, that seem to be the same / similar: error function criterion function cost function objective function I am currently working on ...
1
vote
1answer
34 views

How to implement the regret matching algorithm?

My question is the following: How to calculate the regret in practice? I am trying to implement the regret matching algorithm but I do not understand how to do it. First, I have $n$ players with ...
3
votes
1answer
30 views

Training given pairs of similar values, not labels

I have pairs of "similar" values $(x_i, y_i)$ drawn from a space $x_i, y_i \in S$, and want to train a neural network $N$ such that $N(x_i)$ would be "close" to $N(y_i)$ for all $i$, yet, to make it ...
-1
votes
1answer
14 views

Training Error & Convergence to True Error

I Take some online class for Machine Learning. one of teacher say this sentence. if we have m data points, the training error converges to the true error as m → ∞. i thought, this sentence not ...
0
votes
1answer
28 views

VC Dimension Calculation for Intervals

As i See in ML Course a VC dimension calculation is very theoretical. What is the VC-dimension of intervals in R? The target function is specifieed by an interval, and labels any example positive ...
1
vote
3answers
133 views

Over-fitting Always Occurs?

i get stuck in one sentence in machine learning. i read tom Mitchel book on ML, and some other materials. if we have small training set, always over-fit can occurs? or is likely to occurs? i read ...
-1
votes
1answer
40 views

Policy function π in Reinforcement learning unclear

I have one question about policy function in Reinforcement learning. in fact this function indicates which action should be done in each state? Or this function indicate for get the ...
-2
votes
1answer
42 views

Neural Network Design Challenge

i'm studying for PHD Entrance Exam on Stanford. one of previous material exam designed very challenging. i want to design a NN for classifying following 2-class problem. 1) output should be -1 or ...
1
vote
0answers
17 views

basic doubt on policy iteration

consider the policy iteration algorithm for a finite state MDP. Suppose the initial policy is a stochastic policy. Now, can the optimal policy be deterministic after improvements ? Or, can we say that ...
1
vote
0answers
17 views

If one hypothesis class is a proper subset of another, what is the relation of their VC dimensions?

Assume two hypotheses classes $H_A\subset H_B$ defined over the same instance space $\delta$. Assume also $VC(H_A)=d$, does this mean $VC(H_B)\geq d$ ? where $VC$ is the VC dimension. We can use the ...
0
votes
1answer
37 views

Why is the VC dimension different on intervals and half intervals?

As I read this lecture for being familiar with VC dimension we find on p. 8: VC(half intervals in $\mathbb{R}$ ) = 1 .... no subset of size 2 can be shattered VC(intervals in $\mathbb{R}$ ...
2
votes
2answers
41 views

Why is automatically labeling data in unsupervised learning hard?

I currently studying machine learning and pattern recognition area. Today, my professor said implementing an unsupervised system that automatically labels data is difficult. Why is that? I think if I ...
0
votes
1answer
94 views

Bayesian Nets & Markov Blanket

As i passed PHD entrance exam, some days ago, i want to find solutions for challenging problem. In Bayes network on X={X1,...Xn} each random variable has P parents and Q child's. for Xi we want to ...
0
votes
1answer
18 views

Understanding non-linear dimensionality reduction algorithm (locally linear embedding)

I have a question about Locally Linear Embedding. I am trying to study this algorithm and implement it for better understanding. I have read An Introduction to Locally Linear Embedding. However, I ...
1
vote
2answers
43 views

Need an algorithm to find the input factors that are most affecting the output

I apologize if this question is already answered and appreciate any pointers to existing answers. I'm not familiar with statistical or data mining terms so my search was limited to basic words used in ...
1
vote
1answer
34 views

Can heuristic methods and machine learning approaches be considered alternate methods to solve NP-Complete problems?

I was watching the videos from Skiena's Computational Biology Lectures, which is also available at youtube. In those videos, the professor made a statement that, most of the problems posed to computer ...
0
votes
0answers
29 views

Can anyone help with a simple neural net I am trying to code?

I have a neural net with two input units (and a bias) connected to four hidden units, with each input unit (including the bias) connected to all the hidden units. Then there is one output unit. All ...
0
votes
1answer
20 views

How to use different size features in SVM?

I want to train a support vector machine with some features. The problem is, one of the features is 1-dimensional (only an angle) and the other is an LBP Histogram, an 58-dimensional vector. ...
0
votes
0answers
10 views

A confusion on adaptive algorithm

Consider flight trajectory control problem i.e. find out the control parameter for which the average error of the actual output and desired output is minimized. Can we call any algorithm for solving ...
0
votes
1answer
30 views

Algorithm for cost function maximization

I have a system that takes in 'm' inputs and provides a cost value as an output. The system is a "black box" to me. The inputs can be varied and the corresponding output can be observed, however, I ...
2
votes
0answers
20 views

Non-i.i.d Empirical Risk Minimization [closed]

It's a post which already posted on math.stackexchange.com. I'm not a statistician so please forgive me if I pose a silly question, but it's a real problem for me in my research. Suppose we have ...
3
votes
2answers
55 views

How do learn the most important nodes in a tree?

I have a list of 20000 words and how often they appeared in a set of 500 newspaper articles. I am trying to build a stemmer which chops off suffuxes from each words, so ...
1
vote
1answer
41 views

Q-learning in a Dynamic environment

I am new to reinforcement learning. Lately, I have learned Q-learning using the following tutorial which find great : http://mnemstudio.org/path-finding-q-learning-tutorial.htm If the environment is ...
0
votes
0answers
28 views

Backpropagation Through Time Recursive Algorithm

Would it be plausible to write a recursive version of backpropagation through time for recurrent neural network training? I've only found the iterative version: ...
1
vote
1answer
64 views

Best algorithm for correlation between time series?

I have some biological data (ECG), which are quite chaotic in nature, and and some other data; that are not chaotic but related in some way, like fatigue. I want to find out how the time series, ...
0
votes
1answer
34 views

How to cluster a large movie dataset ??

I have to cluster a movie dataset of 10000 movies. A movie has attributes like Genres, Actors, Directors, Year. Earlier I thought that we can use a simple clustering algorithm like k-medoids and the ...
3
votes
0answers
37 views

What are some of the methods that NLP practitioners use to automatically learn linguistic features from text? [closed]

I am learning about NLP, with an eye to starting some practical NLP projects. I see that many of the algorithms for relation extraction and named entity recognition require you to identify linguistic ...
0
votes
1answer
28 views

What does “finding an optimal action” for a bandit mean?

In Sutton and Barto's reinforcement learning book, in multi-armed bandit problem a phrase has been used. "finding an optimal action" using greedy/$\epsilon$-greedy algorithm. When it is said that an ...
3
votes
1answer
69 views

Why linear transformation can improve classification accuracy when the dimensionality of data is high?

Let $X$ be an $m\times n$ ($m$: number of records, and $n$: number of attributes) dataset. When the number of attributes $n$ is large and the dataset $X$ is noisy, classification gets more ...
1
vote
0answers
27 views

What is linear relaxation in the context of bayesian networks? [closed]

To add onto the question, how are elliptical differential equations applicable in this context? I was listening to a talk about Bayesian networks and someone asked if they were using differential ...
1
vote
2answers
62 views

Can a self-learning appliance be developed?

I have heard of machine learning systems that can learn from trials of data what effect it should have, but I was wondering is it possible to make a learning appliance that builds on past data? ...
2
votes
2answers
114 views

EM algorithm for two Gaussian models

This is about basic machine learning which I do not understand clearly. I have 2 Gaussian models $G_1$ and $G_2$ and given a list of data as below. (1, 3, 4, 5, 7, 8, 9, 13, 14, 15, 16, 18, 23) I ...
2
votes
0answers
28 views

Document clustering for summarization

I am curious as to what steps one would reasonably need to take to perform an extraction-based text summarizer. I've taken a look at some papers I've found on Google such as this one, which explains ...
2
votes
1answer
92 views

Method to recognize abstract objects such as hand-drawn objects?

My research is in the area of Document Image Analysis. To be specific, the topic of my thesis is to automatically recognize and index characters in a set of hand-drawn objects, e.g. given a volume of ...
1
vote
2answers
61 views

Perceptron learning rule doesn't work [closed]

i'm a little bit lost ... can you help me ? So I have this table of date (each row give a point with its group) So i took a random weight let's say : [1, -2] H = 1 if n =< 0 0 otherwise ...
5
votes
2answers
97 views

Unknown notation “$e^T$” in a machine learning paper

I'm trying to understand the material in "A Dual Coordinate Descent Method for Large-scale Linear SVM" by Hsieh et. al. (link to paper) There is an equation for the Dual form of an unconstrained ...
0
votes
0answers
233 views

Haar cascade vs Lbp cascade vs Hog Cascade in object detection

I am doing an project about recognizing one kind of leaf. Well I am using Emgucv with visual stduio 2010 c#. I have read about using 3 differente features extraction but I do not know when I can use ...
1
vote
1answer
46 views

Clustering a matrix into similar groups

I'm working on a problem where I have a matrix of values which I know will be in groups of similarly-valued elements. I am trying to find these groups of similarly-valued elements. I'm going to ...