Questions tagged [machine-learning]

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

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10 views

Help with understanding why we need an expectation in the loss

I am reading the paper SV2P - Stochastic Varaiational Video Prediction (https://arxiv.org/abs/1710.11252). In it the authors use the loss shown in the image: Why do we need expectation in the ...
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32 views

What do we mean by “spectral domain” in the context of graphs?

What do we mean by the spectral domain in the context of graphs? For example, I have heard that graph convolutions are easiest to define in the spectral domain. When it comes to the word "spectral", I ...
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1answer
67 views

Algorithm suggestion for ticket routing system using Machine Learning

Background info I'm a beginner in ML, let me start there. I'm trying to implement an intelligent system that can route a ticket (in a ticketing system), to the appropriate place based on a few ...
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1answer
586 views

Condensed Nearest Neighbor Explanation

I have a question regarding the Condensed Nearest Neighbor algorithm from ...
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20 views

How to go about designing a quiz that changes difficulty based on user performance?

I thought about using a machine learning algorithm to learn the performance patterns of the quiz taker and model the next quiz based on how he/she performed. So each question will have a difficulty ...
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2answers
47 views

Are fully connected layers required for convnets?

I have a reinforcement learning model I'm trying to create for a grid based game. One of the features of the game is that the game board can get bigger mid game, although I know this is a problem that ...
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1answer
42 views

k-means clustered data: how to label newly incoming data

I have a data set with labels that were produced by a $k$-means clustering algorithm. Now there is some data (with the same data structure) from another source and I wonder what is the most sensible ...
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1answer
34 views

point clouds in machine learning

What is the purpose of point clouds in machine learning? Consider the following suggestion: Say I have a table (per year) of records (such as days) each of which is made of n real numbers such as ...
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17 views

how does bagof features work in MATLAB? [closed]

I tried to use machine learnign in matlab using bagoffeatures to captures features and teach the code betwee two types of plots. However, bagofFeatures could not detect ant features. this is my plot: ...
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39 views

Is there any Boosting algorithm with closed-form solutions?

My goal is to formulate the learning and generalization phases of any Boosting algorithm as a matrix-vector operation. Through Google, I found a good pdf (*) describing several boosting algorithms ...
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14 views

PCA collision - finding matrix with different numbers that reduced with PCA to same numbers

I want to find matrix X 2*2: a1 b1 a2 b2 a1!=a2 b1!=b2 so that after im applying PCA on that with number of prinicpal compoments 1 i wish to get matrix 2*1: c c i want to find collision
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1answer
48 views

What does “Temporal extent” mean?

I am reading Long-term Temporal Convolutions for Action Recognition and under the Section 3.1, I read this: To investigate the impact of long-term temporal convolutions, we here study network ...
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1answer
31 views

How do we fix area of detectors in object detection?

I have gone through various articles on medium and also some from other sites trying to understand SSD. I am able to figure out most of the things from articles except this one. They always say that ...
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0answers
26 views

Is the preprocessing process using the tfidf vectorizer really useful for model learning?

I am a student who is studying machine running alone. As far as I know, the Tf-idf Vectorizer is a function that combines the Count Vectorizer and the Tf-idf Transformer. I was wondering if the Tf-idf ...
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1answer
22 views

Is it still transfer learning if you consider input as well as output? (neural networks)

I'm new to the CS stack exchange, so a fond hello to you all! I joined since I have a question I've been curious about. I have recently been running some experiments in transfer learning - ...
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1answer
614 views

Single Layer Perceptron vs Multi Layer Perceptron

Why the single layer perceptron has a linear activation function while the Multi Layer Perceptron has a non-linear activation function ? What is the potential of the Multi Layer Perceptron respect of ...
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1answer
31 views

Can the test set of attributes be a subset of the training set's attributes?

I'm currently writing an application for a trick-based card game, where agents are assigned points based on the accuracy of their predictions of how many hands they're going to win. The number of ...
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76 views

What is the practical limit to how many object classes you can detect with Faster RCNN?

I am trying to follow this tutorial where the Faster-RCNN-Inception-V2-COCO model from TensorFlow's model zoo is used to detect playing cards. I was wondering what is the practical limit to the number ...
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1answer
24 views

what does this phrase mean: “train a policy network”

I am familiar with the basics (and perhaps a substantial amount of basics) of imitation learning and reinforcement learning. In IL (imitation), we take demonstrations from an assumed expert, which we ...
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63 views

Why do mainstream speech models no longer require a personalized training step?

Back in the Windows XP era, when setting up Windows OS-built-in speech/dictation, I had to speak out a bunch of programmed-in text samples to the speech-to-text engine to personalize my voice profile. ...
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17 views

How to add important events as input in neural network?

I'm quite new to neural networks so I apologize if this question is too basic/doesn't really make sense. I have a financial time series dataset and I have a binary variable which is 0 if no important ...
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1answer
54 views

Batch sizing for convolution neural networks — powers of 2 or powers of primes?

The conventional wisdom for convolution neural networks (CNNs) is to make the batch size a power of 2 because of hardware utilization/optimizations done in the convolution layers. A similar logic ...
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32 views

Is a linear classifier convex?

Is the optimization of a linear classifier convex? Is there any local optima or saddle points for a linear classifier?
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22 views

How does neural net complexity relate to other complexity measures?

In neural networks, "weight regularization" is often used as a so called "complexity penalty" in order to make sure that the network generalizes better from training data. Similarly, in "program ...
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86 views

What is the relationship between pairwise loss and centroid loss?

What is the relationship between pairwise loss and centroid loss? Under what conditions you would expect them to give similar behavior? Under what conditions would they give different behavior?
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15 views

How to compute the sample update error?

In the book Reinforcement Learning An Introduction,Chapter 8.5,there is an example that compares the efficiency of expected and sample updates: According to the author, "In this case, sample updates ...
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1answer
34 views

How can I represent the following mathematically? (Eigenfaces reconstrcution)

I got the following from a web site: The feature vectors represent each image as a linear combination of the eigenfaces defined by the coefficients in the feature vector; if we multiply each ...
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48 views

Card dealing problem with constraints (blacklisting),

A friend of mine and I are trying to teach a bot play a card game (bela) We are using monte carlo tree search (MCTS) to estimate the probability of winning hand in regards to multiple possible (!...
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1answer
102 views

(OCR ) How to Recognise Handwritten fractional numbers using Neural networks

I want to be able to recognise handwritten math numbers using images of the numbers , i was able to do create a ANN model for recognising simple decimal numbers , but i have no idea on how to ...
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1answer
125 views

Help needed for understanding proof of No Regret Multi Armed Bandit Algorithm

I was reading Elad Hazan's book on Online Convex Optimization(http://ocobook.cs.princeton.edu/OCObook.pdf) and am facing difficulty understanding the proof given for the No regret algorithm for MAB (...
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1answer
66 views

Do data points mean Eigenfaces in higher dimensional space?

I saw the following animation at making sense of PCA , which shows blue data points. I am reading a paper on Eigenfaces which says that: "a typical image of size 256 by 256 becomes a vector of ...
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61 views

Machine learning for VLSI floorplanning tool

I have an educational assignment to make an VLSI floor-planning tool. Can I use machine learning in some part of the algorithm? For example, I was reading the book Algorithms for VLSI Physical Design ...
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1answer
150 views

What is the difference in SMO algorithm for SVM and SMO for one class?

Please let know if this is not the correct forum to ask this question. If not can anyone please tell where can I ask this question? I am trying to understand the difference between the paper : https:/...
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1answer
35 views

Problem with Understanding “correlated attributes into a set of values of uncorrelated attributes” in PCA

I am studying PCA. I have a problem in understanding the following concept: What is meant by transforming "correlated attributes into a set of values of uncorrelated attributes" in Principal ...
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28 views

Is there an equivalent of “control flow” in deep learning systems?

Traditional programs work significantly through control flow. I know that there are simple algorithms that have no control flow at all (i.e. they just perform a fixed sequence of executions), but I ...
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1answer
74 views

Show that the Laplace smoothing for bigrams is a valid probability distribution

If we consider any smoothing technique like laplace or delta smoothing. Intuitively we can see that the we are stealing from sequences with non zero probablity and re distribute to sequences with zero ...
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0answers
122 views

Proof of perceptron convergence theorem for ZERO threshold?

The generalized perceptron convergence theorem is for a defined threshold T. When you do the maths it all comes to an upper bound and a lower bound. The lower bound looks like this! Therefore ...
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1answer
57 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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1answer
44 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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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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1answer
37 views

Matching/finding mathematical plot images

I'm trying to come up with a method to match a given mathematical plot against a database of other plots. To make it more specific: plots are generated in R as PNG and might have different dimensions. ...
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1answer
27 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 ...
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1answer
38 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 ...
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1answer
23 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, ...
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1answer
474 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
40 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
452 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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3answers
1k 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 ...
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0answers
32 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
238 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 ...