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Questions tagged [machine-learning]

For questions related to machine learning (ML), which is a set of methods that can automatically detect patterns in data, and then use the uncovered patterns to predict future data, or to perform other kinds of decision making under uncertainty (such as planning how to collect more data). ML is usually divided into supervised, unsupervised and reinforcement learning. Deep learning is a subfield of ML that uses deep artificial neural networks.

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16 votes
1 answer
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Will parameter sweeping on one split of data followed by cross validation discover the right hyperparameters?

Let's call our dataset splits train/test/evaluate. We're in a situation where we require months of data. So we prefer to use the evaluation dataset as infrequently as possible to avoid polluting our ...
Philipp Cannons's user avatar
7 votes
1 answer
154 views

How does the network know which objects to track in the paper "Label-Free Supervision of Neural Networks with Physics and Domain Knowledge"?

I was reading the paper Label-Free Supervision of Neural Networks with Physics and Domain Knowledge, published at AAAI 2017, which won the best paper award. I understand the math and it makes sense. ...
sanjeev mk's user avatar
6 votes
0 answers
110 views

$\frac{P(x_1 \mid y, s = 1) \dots P(x_n \mid y, s = 1) P(y \mid s = 1)}{P(x \mid s = 1)}$ indicates that naive Bayes learners are global learners?

I am currently studying the paper Learning and Evaluating Classifiers under Sample Selection Bias by Bianca Zadrozny. In section 3. Learning under sample selection bias, the author says the following: ...
The Pointer's user avatar
6 votes
0 answers
148 views

Are there any easy ways to create annotated training images for object detection?

For the purposes of object detection, are there any easy ways to create annotated training images? For example, if we have $10,000$ images and want to draw bounding boxes on 2 objects for each image, ...
James's user avatar
  • 71
6 votes
1 answer
235 views

How do big companies, like Facebook, model individuals and their interaction?

As a layman in AI, I want to get an idea of how big data players, like Facebook, model individuals (of which they have so many data). There are two scenarios I can imagine: Neural networks build ...
Hans-Peter Stricker's user avatar
6 votes
1 answer
393 views

Which neural networks are suitable for visual place recognition?

I am doing a project on visual place recognition in changing environments. The CNN used here is mostly AlexNet, and a feature vector is constructed from layer 3. Does anyone know of similar work ...
Daniel Wong's user avatar
5 votes
1 answer
152 views

Correcting 'bad' translations in a sequence-to-sequence neural machine translation model

In working with basic sequence-to-sequence models for machine translation I have been able to achieve decent results. But inevitably some translations are not optimal or just flat-out incorrect. I am ...
jrthom18's user avatar
4 votes
1 answer
218 views

What is 'fairness' in machine learning?

How does one define the concept of fairness in machine learning? I've seen the term lots of times but never used it myself in research (1, 2). Is there a generally agreed-upon definition of fairness ...
Robin van Hoorn's user avatar
4 votes
2 answers
243 views

Which neural network can I use to solve this constrained optimisation problem?

Let $\mathcal{S}$ be the training data set, where each input $u^i \in \mathcal{S}$ has $d$ features. I want to design an ANN so that the cost function below is minimized (the sum of the square of ...
user3489173's user avatar
4 votes
0 answers
545 views

When computing the ROC-AUC score for multi-class classification problems, when should we use One-vs-Rest and One-vs-One?

The sklearn's documentation of the method roc_auc_score states that the parameter multi_class can take the value ...
Leockl's user avatar
  • 151
4 votes
1 answer
343 views

NEAT can't solve XOR completely

I'm currently implementing the NEAT algorithm. But problems occur when testing it with problems which don't have a linear solution(for example xor). My xor only produces 3 correct outputs once at a ...
Creepsy's user avatar
  • 141
4 votes
0 answers
131 views

Could zero-padding affect learning in a negative way?

I implemented an LSTM with Keras to perform word ordering task (given a syntactically unordered sentence, the goal is to label ...
pairon's user avatar
  • 143
4 votes
0 answers
141 views

Is there a mathematical formula that describes the learning curve in neural networks?

In training a neural network, you often see the curve showing how fast the neural network is getting better. It usually grows very fast then slows down to almost horizontal. Is there a mathematical ...
zooby's user avatar
  • 2,216
4 votes
0 answers
147 views

What are stable ways of doing online machine learning?

I am trying to deploy a machine learning solution online into an application for a client. One thing they requested is that the solution must be able to learn online because the problem may be non-...
Rui Nian's user avatar
  • 433
4 votes
0 answers
116 views

How do the relative number of cells between neighboring stacked LSTM layers affect the network's behavior?

It seems that stacking LSTM layers can be beneficial for some problem settings in order to learn higher levels of abstraction of temporal relationships in the data. There is already some discussion on ...
adamconkey's user avatar
4 votes
0 answers
218 views

What characteristics make it difficult for a Neural Network to approximate a function?

What are the characteristics which make a function difficult for the Neural Network to approximate? Intuitively, one might think uneven functions might be difficult to approximate, but uneven ...
user avatar
4 votes
0 answers
61 views

What is the motivation for row-wise convolution and folding in Kalchbrenner et al. (2014)?

I was reading the paper by Kalchbrenner et al. titled A Convolutional Neural Network for Modelling Sentences and I am struggling to understand their definition of convolutional layer. First, let's ...
Tomasz Garbus's user avatar
4 votes
0 answers
2k views

Why did fuzzy logic fall out of fashion?

Fuzzy logic seemed like an active area of research in machine learning and data mining back when I was in grad school (early 2000s). Fuzzy inference systems, fuzzy c-means, fuzzy versions of the ...
Alex S King's user avatar
4 votes
0 answers
92 views

Does overfitting imply an upper bound on model size/complexity?

Suppose that I have a model M that overfits a large dataset S such that the test error is 30%. Does that mean that there will always exist a model that is smaller and less complex than M that will ...
Shehryar Malik's user avatar
4 votes
0 answers
677 views

Is there any way and any reason why one would introduce a sparsity constraint on a deep auto-encoder?

Is there any way and any reason why one would introduce a sparsity constraint on a deep autoencoder? In particular, in deep autoencoders, the first layer often has more units than the dimensionality ...
MattSt's user avatar
  • 597
4 votes
0 answers
131 views

Supervised K-means clustering doesn't appear to work

I have a data set containing actions taken by customers (e.g., view a product, add a product to cart, purchase product), the product bought (if any) and times of said actions. I am attempting to use K-...
Jessica Chambers's user avatar
4 votes
4 answers
1k views

Use Machine/Deep Learning to Guess a String

I want to be able to input a block of text and then have it guess a string within a predefined range (i.e. a string that starts with three letters and ends with five numbers like "XXX12345", etc). ...
TreHoffman's user avatar
4 votes
0 answers
192 views

How to feed a variable size sequences into a CNN?

If I want to train a convoluted NN on time series but I cannot decide where to split the data. I see that other people use a jumping window over the input. so the feed say 20 sec of observation as 1 ...
Boppity Bop's user avatar
4 votes
1 answer
810 views

Traveling salesman problem variant: which algorithm to choose?

I have an industrial problem which I'm trying to cast as a Traveling Salesman problem (TSP) in 3D euclidian space. There are physical limitations which implies that some subpaths may or may not be ...
Oliver's user avatar
  • 41
4 votes
2 answers
100 views

How should I select the features for predicting diseases (in particular when patients specify their health issues)?

My aim is to train a model for predicting diseases. Now, according to this Wikipedia article, diseases are classified based on the following criteria in general: Causes (of the disease) Pathogenesis (...
Muhammad Maqsoodur Rehman's user avatar
3 votes
0 answers
68 views

Which algorithm for production scheduling with multiple goals - alternative for genetic algorithm

I am currently using a genetic algorithm for optimising the production schedules of a factory that produces bespoke insulation panels. The factory has a list of bespoke panels that need to be produced ...
Dirk V.'s user avatar
  • 31
3 votes
0 answers
128 views

How can i tinker my neural network to learn stronger on rare events?

I am training a neural network on a regression problem. Most of the time the actual y (label) has the same value (say ~0.2) and only in rare cases the actual y is very different (say 2.0 or -2.0) ...
Carl Philip's user avatar
3 votes
1 answer
382 views

For which problem sizes is Deep Q-Learning suitable and why?

I am wondering for which problem sizes a Deep Q-Learning algorithm is most appropriate. For example, whether it is particularly suited for low complexity problems or not for high complexity problems. ...
user avatar
3 votes
0 answers
41 views

How should I compare multiple machine learning models to be (generally) fair to all models?

I am testing multiple models on IBM HR Analytics Attrition Dataset (1470 lines) and HR Analytics dataset (15000 lines) for a research project. The models include traditional models (Naive Bayes, SVM), ...
Đào Minh Dũng's user avatar
3 votes
1 answer
143 views

If I can repeat ML experiments, how can I bound my results?

It has been asked here if we should repeat lengthy experiments. Let's say I can repeat them, how should I present them? For instance, if I am measuring the accuracy of a model on test data during some ...
biofa.esp's user avatar
3 votes
0 answers
172 views

Which algorithms are used to locate objects in a 3d space?

I can see mobile apps that can locate a 3D object on a surface with a mobile camera and you can turn around that object. What is the name of the algorithm(s) that is used for that purpose? Or, is ...
dasmehdix's user avatar
  • 257
3 votes
1 answer
165 views

Is there a way to update the neural network to fit the new data without the time required for retraining?

I built a basic neural network in MATLAB. The neural network classifies points on the X-Y axis system into two classes (0 and 1). (I try to get the function that represents a shape from this photo) ...
shlomo odem's user avatar
3 votes
2 answers
605 views

Is $(y_i - \hat y_i)x_i$, part of the formula for updating weights for perceptron, the gradient of some kind of loss function?

A post gives a formula for perceptron to update weights I understand almost all the parts of it, except for the part $(y_i - \hat y_i)x_i$ where does it come from? Is it the gradient of some kind of ...
JJJohn's user avatar
  • 221
3 votes
0 answers
418 views

Loss function to minimize the distance between sets

Are there references or links to examples about loss functions "Distance Metrics" which could be used to minimize the distance between two sets for a neural network. More precisely, this ...
Noah16's user avatar
  • 131
3 votes
0 answers
91 views

Why is the margin attained with $\Phi=\left[2 x, 2 x^{2}\right]^{T}$ greater than the margin attained with $\Phi=\left[x, x^{2}\right]^{T}$?

I am trying to understand the solution to part 4 of problem 3 from the midterm exam 6.867 Machine learning: Mid-term exam (October 15, 2003). For reproducibility, here is problem 3. We consider here ...
user871621's user avatar
3 votes
0 answers
317 views

Image classification - Need method to classify "unknown" objects as "trash" (3D objects)

We have an image classifier that was built using CNN with faster R-CNN and Yolov5. It is designated to run on 3D objects. All of those objects have similar "features" structure, but the ...
Stackaloo's user avatar
3 votes
0 answers
205 views

Can XGBoost solve XOR problem?

I've read that decision trees are able to solve XOR operation so I conclude that XGBoost algorithm can solve it as well. But my tests on the datasets (datasets that should be highly "xor-ish"...
GKozinski's user avatar
  • 1,280
3 votes
1 answer
596 views

What's the difference between domain randomization and domain adaptation?

In my understanding, domain randomization is one method of diversifying the dataset to achieve a better shot at domain adaptation. Am I wrong?
Taro Yehai's user avatar
3 votes
0 answers
186 views

What is the difference between fuzzy neural networks and adaptive neuro fuzzy inference systems?

I have, like you see, just a general question about the combination of fuzziness and neural networks. I understood it as follows Fuzzy neural networks as a hybrid system: the neural network helps me ...
Eli Hektor's user avatar
3 votes
0 answers
65 views

Is maximum likelihood estimation meaningless for a dataset of only outliers?

From my understanding, maximum likelihood estimation chooses the set of parameters for the estimator that maximizes likelihood with the ground truth distribution. I always interpreted it as the ...
ashenoy's user avatar
  • 1,419
3 votes
0 answers
122 views

Do I have to downsample the input and upsample the output of the neural network when implementing the NICE algorithm?

Consider that my input is an RGB image. The size of my image is $N\times N$. I'm trying to implement NICE algorithm presented by Dinh. The bijective function $f: \mathbb{R}^d \to \mathbb{R}^d$ maps $X$...
bitWise's user avatar
  • 173
3 votes
0 answers
89 views

Why is the loss associated with my neural network increasing?

I am currently learning neural networks using data from Touchscreen Input as a Behavioral Biometric. Basically, I am trying to predict "User ID" by training the neural network model shown ...
onexpeters's user avatar
3 votes
1 answer
166 views

How do I poison an SVM with manifold regularization?

I'm working on Adversarial Machine Learning, and have read multiple papers on this topic, some of them are mentioned as follows: Poisoning Attacks on SVMs: https://arxiv.org/pdf/1206.6389.pdf ...
boomselector's user avatar
3 votes
0 answers
50 views

In machine learning, how can we overcome the restrictive nature of conjunctive space?

In machine learning, problem space can be represented through concept space, instance space version space and hypothesis space. These problem spaces used the conjunctive space and are very restrictive ...
aitsamahad's user avatar
3 votes
0 answers
567 views

Can Bert be used to extract embedding for large categorical features?

I've lot of training data points (i.e in millions) and I've around few features but the issue with that is all the features are categorical data with 1 million+ categories in each. So, I couldn't use ...
user_12's user avatar
  • 149
3 votes
0 answers
1k views

Why isn't there a model playing FPS like CoD or Battlefield already existing?

Assuming we had an unlimited time to train a model and a very powerful machine to use our model in real-time (hello quantum computer), I'd like to know why no one could achieve to build an AI able to ...
politinsa's user avatar
  • 131
3 votes
0 answers
55 views

Rarely predict minority class imbalanced datasets

I have a dataset in which class A has 99.8%, class B 0.1% and class C 0.1%. If I train my model on this dataset, it predicts always class A. If I do oversampling, it predicts the classes evenly. I ...
Johnny P.'s user avatar
3 votes
0 answers
177 views

DQN, how to choose the reward fucntion?

I built a simple AI system that tries to solve the 8 puzzle using DQN. The problem is, if the agent gets only a reward greater than zero when winning, the training will take a long time, so I made a ...
j4at's user avatar
  • 131
3 votes
0 answers
101 views

Which machine learning algorithms can be used to build a recommendation system?

I am working on building a recommendation engine. I need to build a model that recommends similar items. Currently, I am using the Nearest Neighbor algorithm present in ...
Harshith's user avatar
  • 131
3 votes
0 answers
40 views

Which hyper-parameters are considered in neural architecture search?

I want to understand automatic Neural Architecture Search (NAS). I read already multiple papers, but I cannot figure out what the actual search space of NAS is / how are classical hyper-parameters ...
cocojambo's user avatar

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