# 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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### Hand Landmark Coordinate Neural Network Not Converging

I'm currently trying to train a custom model with tensorflow to detect 17 landmarks/keypoints on each of 2 hands shown in an image (fingertips, first knuckles, bottom knuckles, wrist, and palm), for ...
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### RMSProp Momentum and Decay

I'm making an application of MobileNetV2 and according to their article: We train our models using TensorFlow. We use the standard RMSPropOptimizer with both decay and momentum set to 0.9. We use ...
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### what do i need to consider writing a python script that uses a pre-trained model with new incoming data

I have completed and saved(with joblib) a trained model to do with detecting messages that exerts pressure. I understand that for me to use the model I would need to use joblib again to deploy my ...
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### How to calculate the prior covariance matrices in "Interactive Text Ranking with Bayesian Optimization"? (A Gaussian Process used for Q&A)

My question is about the article Interactive Text Ranking with Bayesian Optimization A Case Study on Community QA and Summarization, which uses Stochastic Variational Inference described in the paper ...
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### Explain why there is no need to invert a Covariance Matrix in this Gaussian Process

My question is about the article Scalable Bayesian preference learning for crowds. The paper describes the use of Stochastic Variational Inference (SVI) for solving the problem called Preference ...
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### How to write code for levy flight in cuckoo search

I want to write levy flight random number distribution code for cuckoo search optimization. So how to select randomly two instances from set of instances by levy flight.
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### Proof of Calculating VC-Dimensions

I still have some doubts for finding the VC-dimension. Suppose $\mathcal{H}$ has VC-dimension $n$. This is the process of how I think about it: (1) Show that there is a set of $n$ points that can be ...
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### PAC Learnability of Infinite Hypothesis Classes

Is it true that for a finite or a countably infinite hypothesis class $\mathcal{H}$, then it is going to be PAC-learnable (and vice-versa)? And what about if we change the cardinality of the ...
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### What is the best learning to hashing for embedding points in a Vector Space in Hamming Space?

I have a cloud of points in $\mathbb{R}^n$ and I want to embed them in Hamming Space. One possible solution is for example found in Inductive Hashing on Manifolds. The problem is: I need an extremely ...
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### Can we supervise on the hidden states of RNN?

I'm trying to generate some history-dependent model with machine learning, whose underline physical model has a clear definition of its "internal state variable" (a state derived from ...
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### Learning algorithms- difference between a learner (the algorithm) having continuous access to the samples (oracle) vs getting all at start

Is there any fundamental difference between learning algorithms e.g. variants of PAC which have continuous access to examples on which to train (i.e. these are obtained as the algorithm runs, when ...
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### Using Restricted Boltzmann Machines for clustering data

I want to use RBMs as a clustering model and the idea is to use an RBM for clustering a 16 class clustering problem with 4 nodes in the hidden layer. The clustering is done by updating the hidden ...
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### Describing a consistent learner

Let $X=R^3$. Let $C=H=\{h(a,b,c)=\{(x,y,z) |x|\leq a,|y|\leq b, |z|\leq c\}, a,b,c\in R_+\}$ the set of all origin centered boxes. Describe a polynomial sample complexity algorithm that learns $C$ ...
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### Why does it take O(n!) time to specify a canonical ordering for learning flatten adjacency matrices/graphs?

I was reading a paper for learning graphs (paper is GraphRNN) and it says in section 2.2 (emphasis by me): Vector-representation based models. One naive approach would be to represent G by flattening ...
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### How many pixels support each neuron in multi-layer CNN?

I'm studying for a computer vision module and I'm on the deep learning topic, in one past paper we have the following question: Given that a convolutional neural network has five convolution layers (...
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### Applications of derivative only, zeroth-order free optimization

I understand what is derivative-free optimization, and I am thinking a similar problem where the function $f$ we are optimizing is unknown and the only information we can acquire is the derivative. In ...
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### What are open-loop and closed-loop modes of neural networks?

I came across the following line in the book ‘Deep Learning (Ian Goodfellow) 10.2.1, pg 374; The disadvantage of strict teacher forcing arises if the network is going to be later used in an open-loop ...
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### What is the relation between the compatibile features and the state features in Actor Critic Algorithm?

According to Actor-Critic algorithm, $\psi_{\theta}=\nabla_{\theta}\ln \mu_{\theta}(s, a)$ where $\mu_{\theta}(s, a)$ is the policy followed by the actor and $\psi_\theta$ is the compatibile features ...
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### Find the exactly correct separating hyperplane of SVM when the data is not perfectly linearly separable

I am thinking about the following case where the data in region 1 is always positive and the data in region 2 is always negative, but the data in region 3 can be both positive and negative. Are there ...
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### How to transform an Abstract Syntax Tree (AST) to an Abstract Binding Tree (ABT)? (for machine learning fo theorem proving)

I was reading the HOList paper that applies Graph Neural Networks (GNNs) to the HOL Light (HOList) data set and benchmark for ML for theorem proving. They describe their results etc but there is no ...
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### Reference selection for rating assignment based on pair comparison

Background: a set of 300 images are prepared, randomly pair compared with 60 other images, assigned a rating (from 1-star to 5-star) based on the pair comparison score (+1 if wins a pair comparison ...