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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Is there any way to remove background of an image fully with the help of post-processor techniques(like edge detector) after deep learning based model

I'm using a deep learning-based model (deep lab v3+ with xception as the backbone) for image segmentation and removing the background. The subject of the image will be a person. And my target is to ...
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Which AI model to analyse and organize a random document?

I'm new to ML and AI. I am working on a machine learning project where I create a model that is able to analyze and organize a random document. Now I've been doing a lot of research in this field, but ...
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1answer
25 views

Can RL still learn in a scenario where current state and the next state are independant?

I am trying to implement reinforcement learning into my real-world problem. One thing making me hesitant to apply RL is that this real-world problem of mine is unique in a way how every state is ...
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20 views

Feature Descriptor for Range Doppler Maps

I would like to know which is the best feature descriptor for a sequence of Range Doppler Maps: I have some suggestions like hog features, haar features, SIFT and SURF. Any other suggestion? For the ...
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26 views

Connection between multi-label classification and multi-class classification

For a dataset with multi-label judgment, e.g., coco dataset but where we only want to predict the most possible label. There're multiple ways: train as multi-label learning and predict as a multi-...
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1answer
57 views

PyTorch `torch.no_grad` vs `torch.inference_mode` [closed]

PyTorch has new functionality torch.inference_mode as of v1.9 which is "analogous to torch.no_grad... Code run under this ...
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1answer
38 views

What kind of algorithm or approach can I use to find a specific type of object in an image?

What kind of algorithm or approach can I use to find a specific type of object in an image? In particular, I am interested in finding an object like a windmill in an image taken, for example, from ...
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1answer
97 views

How to decide a train-test split?

In almost every ML model, a train-test (or train-test-val split) is critical to assess the model's performance. However, I have always wondered what the rationale is to decide a particular train-test ...
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1answer
21 views

A recommender system based on millions of fields including text and number

I want to train a model based on millions of fields, including text and number, that are stored in a SQL database and recommend a perfect match based on some inputs. Now, which algorithm is the best ...
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1answer
24 views

Educational Resources and Programming Languages for AI & ML [closed]

I am a Mathematics graduate who is interested in AI and Machine Learning. I would like to dig deep into the maths of them but I do not know where to start. It seems Linear Algebra is the most crucial ...
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9 views

How to create edge detection dataset similar to BIPED dataset [closed]

I would like to create my own dataset for edge detection Models may i know how to annotate images similar to BIPED dataset
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1answer
27 views

What is the best open source python repo for facial recognition? [closed]

I am looking for best open source python repo for facial recognition. Best if it uses tensorflow backend. I know you can train images to recognize. Yolo can be used if trained on face. To name the ...
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Multi-Modal Vs Multi-View learning

What is the difference between Multi-modal & Multi-view in the context of visual data analysis(images) knowing that Multi-view learning deals with Multi descriptors of image.
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Why can't perceptrons approximate any function, in contrast to multilayer perceptrons? [duplicate]

What is the formal explanation and proof that multilayer perceptrons are universal approximators, as opposed to the single layer perceptron. This intutively makes sense to me, I would just like the ...
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12 views

How sensitive are LSTM's to random zero values in its target feature when training?

I have worked with lstm's in the past, specifically for time series forecasting. However, the target feature in these time series were relatively "stable". With the loosely defined "...
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23 views

How do you decide that you have tested enough hyper-parameter combinations for a specific neural network architecture?

How do you decide that you have tested enough hyper-parameter combinations for a specific neural network architecture to discard it and move on to a new model? Do you have a structured (generic) ...
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1answer
36 views

Can I use Sentence-Bert for embedding for fake news detection?

What are the benefits of Sentence-Bert for Sentence Embedding vs other Embedding models like Bert?
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26 views

How to proof that the square of the half-margin of maximum-margin SVM is equal to the summation of lagrange multipliers given by SVM dual?

Can be show that the square of the half-margin of maximum-margin SVM is equal to the summation of Lagrange multipliers given by SVM dual? i.e, Let $ \rho = \dfrac{1}{w}\\ $ Show that: $$ \dfrac{1}{\...
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26 views

Should training be done in number of episodes or number of timesteps?

In the past few deep reinforcement learning projects I've worked with, a problem I have encountered is whether to frame training time in terms of number of episodes or number of timesteps. For ...
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4answers
2k views

How can I predict the next number in a non-obvious sequence?

I've got an array of integers ranging from -3 to +3. Example: [1, 3, -2, 0, 0, 1] The array has no obvious pattern since it represents bipolar disorder mood swings. What is the most suitable approach ...
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23 views

Is there any research on AI as information curator for another AI? [duplicate]

Specialist systems, a form of AI, require big volumes of data for training, and the work of compiling such data is mostly human. Since there already are AI tools to analyze text, would be feasible to ...
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30 views

Which method can accurately detect circular/angular shapes? (attached example)

Is there a method to detect shapes like these accurately and efficiently? I have tried the OpenCv Haar Casacade Classifier which does not work well. These shapes should all be the same class object ...
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1answer
43 views

Appropriate ML algorithm to solve a cutting pattern problem

I have a rectangular area, where I need to place some 2 dimensional geometrical shapes - like a square or circle or a little more complicated shapes. And after the arrangement these shapes should be ...
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17 views

Algorithm to separate audio source that Andrew Ng did in his ML Course

Hey I was doing the ML course of Andrew Ng's ML course. In a video he shows a algorithm that can separate two audio source and separate voice from music. Has any one tried such an algorithm? Though he ...
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19 views

"Hot Word Detection", bur for different applications

I have been looking in detecting a specific rhythm/pattern within the temporal domain for a time-series signal. For this purpose, how "Wake Up" words work for devices like Alexa have gained ...
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0answers
24 views

Recommended way to spilt image sequence for training/validation/testing

For object detection tasks I have a few minutes of video footage from a surveillance camera, converted to a sequence of images and ground truth bounding boxes for all people walking by. Now what's the ...
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1answer
29 views

How do you handle unbalanced image datasets?

I have an image data set on which I am training a CNN. The data set is slightly unbalanced. So, my solution up till now was to delete some images of the majority class. But I now realize that there ...
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20 views

How to assess the goodness of a text generation algorithm

Take a RNN network fed with Shakespeare and generating Shakespeare-like text. Once a model seems mathematically fine, as can be assessed by observing its loss and accuracy over training epochs, how ...
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1answer
40 views

How to handle invalid actions for next state in Q-learning loss

I am implementing an RL application in an environment with illegal moves. For handling the illegal moves, I am currently just picking an action as the maximum Q-value from the set of legal Q-values. ...
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20 views

Multiple GRU layers to improve a text generation

I am using the model in this colab https://colab.research.google.com/github/tensorflow/text/blob/master/docs/tutorials/text_generation.ipynb#scrollTo=AM2Uma_-yVIq for Shakespeare like text generation. ...
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12 views

Identify Merchants from Transaction Dataset

I have a transaction dataset, each transaction is in an unstructured format. The objective is to identify merchant from each transaction. If we look it from NER point of view, there would be problem ...
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1answer
29 views

How to show $\rho > 0$ when $\rho$ be minimum attainable from $y_n(W^{*T}X_n)$, where $W^*$ the vector that separates the data?

In the book Learning from Data written (by Abu Mostafa), we have the following exercise: Let $\rho$ be minimum attainable from $y_n(W^{*T}X_n)$ where $W^*$ is the vector that separates the data. Show ...
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1answer
41 views

How to find "relationships" between two data representations?

I am a researcher in a field, and new to the whole of AI and machine learning techniques. May the following question is trivial or not framed in the ML language but I try my best. I have two sets of ...
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20 views

NLP problem Phrase/Token labeling

Looking for suggestions on how to define the following NLP problem and different ways in which it can be modeled to leverage machine learning. I believe there are multiple ways to model this problem. ...
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2answers
34 views

Why do the authors of the T5 paper say that the "architectural changes are orthogonal to the experimental factors"?

Here's a quote from the T5 paper (T5 stands for "Text-to-Text Transfer Transformer") titled Exploring the Limits of Transfer Learning with a Unified Text-...
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23 views

Machine learning with raw data alone / or raw data with its statistics

My question is very general and it does not originate from a specific problem. Let's assume that, through experience, we have learned that some statistical property of a set of data is important in ...
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1answer
63 views

How do I prepare this 3D data for NN?

How do I prepare the info of 3D models to use with NN? For example, I have thousands of models with boxes similar to the ones in the image below. I can extract the vertices and their normals that make ...
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49 views

What are the different possible usages of the word "i.i.d" in machine learning?

The acronym "iid" stands for "independent and identically distributed". It is a property of a sequence of random variables. You can read here for more details. This question is ...
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17 views

Discrepancy of backpropagation formula between Andrew Ngs ML Course and those derived by neuralnetworksanddeeplearning.com

I'm currently working through Week 5 of Andrew Ngs Machine Learning course on Coursera, which goes through the backprop algorithm for basic neural networks. Whilst trying to derive the formulae he ...
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3answers
74 views

Is the inductive bias always a useful bias for generalisation?

Is it true that a bias is said to be inductive iff it is useful in generalising the data? Or does inductive bias can also refer to the assumptions that may cause a decrease in performance? Suppose I ...
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1answer
58 views

Different ways to calculate backpropagation derivatives, any difference?

I'm studying error backpropagation in neural networks. I am interested in why we use only one path on the computational graph to get the value of the derivative for a weight? I ask the question ...
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2answers
95 views

What is the formal definition for manifold in artificial intelligence?

We come across the word "manifold" in artificial intelligence, especially in the domains where learning is done based on data instances. What is the formal definition for manifold?
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31 views

When can we call a loss function "adaptive"?

A loss function is a measure of how bad our neural network is. We can decrease the loss by proper training. I came across the phrase "adaptive loss function" in several research papers. For ...
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17 views

Is it possible to train parameters engaged in more than two loss functions?

the images are from the paper titled Hi-CMD: Hierarchical Cross-Modality Disentanglement for Visible-Infrared Person Re-Identification by Seokeon Choi et al. as you can see in the first picture p1 ...
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22 views

Why labeling facades?

In Pix2Pix by Isola et al. they translate images from different pairs of image categories to one another. While most other example applications for the algorithm make sense to me, I'm having ...
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0answers
23 views

Alternative chatbot service with export intent/entities function like DialogFlow? [closed]

I've been searching for a chatbot-building website with exportable intents/entities to a particular format (Spreadsheet, CSV, JSON, etc.). But the chatbots I have found so far like Flow.ai or ChatFuel ...
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26 views

Machine Learning Algorithm for OCR on full pages of text

I would like to build an OCR application. In. particular, I want my algorithm to scan entire pages of text in a specific niche language. I was therefore wondering if there are some algorithms that ...
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1answer
46 views

Get the name of a merchant from records

I have a bunch of bank transaction records from which I want to extract merchants' names. In a few subsets of these records, the structure of the string is the same within the subset with only the ...
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1answer
33 views

What is the fundamental difference between the synthesis task and sampling task?

Among the list of tasks in machine learning, synthesis and sampling is one of the key task. Consider the following explanation regarding synthesis and sampling task from Chapter 5: Machine Learning ...
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1answer
32 views

Can I always interpret features as random variables in machine learning safely?

Consider the following statements from Chapter 5: Machine Learning Basics from the book titled Deep Learning (by Aaron Courville et al.) Machine learning tasks are usually described in terms of how ...

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