Questions tagged [machine-learning]

For questions about how quantum computing could improve or affect machine learning i.e. quantum machine learning. Questions about classical machine learning belong on another site, such as Stack Overflow, Cross Validated or Artificial Intelligence SE.

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QML: “Quantum Data loader” instead of QRAM?

In last year‘s conference "Quantum For Business 2019" Iordanis Kerenidis gave a nice talk about quantum machine learning. At about time 27:10 he mentions a "Quantum Data loader" as an alternativ for ...
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What does the maximum of a Hamiltonian means (in a particular paper)?

In the paper Quantum Observables for continuous control of the Quantum Approximate Optimization Algorithm via Reinforcement Learning, an Hamiltonian is defined in order to solve the MAXCUT problem : $...
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Understanding SGD on a Quantum Circuit

I implemented the following circuit, a very simple circuit: I applied the technique presented on Farhi's paper - which I am so happy people in here are talking about more and more ! - and applied to ...
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30 views

Quantum Noise Dataset

Does anyone in here know of an open source source for finding noisy data from quantum gates. I am interested in playing around with in the same way people play around with MNIST. I know it's a long ...
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80 views

How to decompose a multi-target controlled gate?

I'm trying to replicate with qiskit the results of this paper in which basically they implement a quantum version of the Principal Component Analysis applying Quantum Phase Estimation algorithm in ...
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Does anyone know how to get a list of all the Qiskit ML datasets, and if they can also be used for classical machine learning?

I am trying to create a Quantum Classifier and would like to try to test it out using a Qiskit ML dataset. However, I only know of the breast cancer dataset and I would like to try it on another ...
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Introductory material for quantum machine learning

In the past few days, I have been trying to collect material (mostly research papers) related to Quantum machine learning and its applications, for a summer project. Here are a few which I found ...
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Is Industry or PhD programs best for someone wanting to go to quantum machine learning? [closed]

Is Industry and the companies including IBMa and D-wave etc or PhD research programs best for someone wanting to go to quantum statistical/mathematical machine learning in the United States? I mean ...
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Software for implementing Quantum Machine Learning

I want to have a software product specifically suited for Quantum Machine Learning. Please help me with a list of software product which has been designed specifically for implementing Quantum Machine ...
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41 views

What are the mathematical prerequisites to study machine learning on quantum computers?

Besides machine learning, quantum info theory, optimization, and statistics knowledge, what are the prerequisites to implement existing ML techniques and create new ML techniques that would work on a ...
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Variances of the principal components in Ewin Tang's PCA algorithm

In Quantum-inspired classical algorithms for principal component analysis and supervised clustering, the PCA algorithm requires that the variances of the principal vectors differ by at least a ...
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1answer
147 views

Quantum PCA State Preparation

In Quantum Algorithm Implementations for Beginners is an example of the Quantum PCA with an given 2 x 2 covariance matrix $\sum$. The steps for state preparation are given in the paper. The steps are: ...
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Pennylane and Qiskit for quantum machine learning

I'm interested in quantum computing, specifically in “quantum machine learning” (QML). I'm going to start my masters program in computer science and have previous experience in classical machine ...
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Quantum speedup in Bayesian machine learning on NISQ computers

It is well known that in Bayesian learning, applying Bayes' theorem requires knowledge on how the data is distributed, and this usually requires either expensive integrals or some sampling mechanism, ...
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How to preprocess data to fit Qiskit QSVM

I want to start experimenting with quantum machine learning using Qiskit library, but I have come across an issue. All tutorials I have seen so far like this one import datasets using custom packages. ...
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Will deep learning neural networks run on quantum computers?

Deep Learning (multiple layers of artificial neural networks used in supervised and unsupervised machine learning tasks) is an incredibly powerful tool for many of the most difficult machine learning ...
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What language is more suitable for quantum machine learning algorithms?

What language is more suitable for quantum machine learning algorithms? Is it right that it's Python + Pyquil? Or something else? And do you know the sources where you can see the sample codes of ...
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1answer
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Low-dimensional data and quantum machine learning

Ewin Tang says to not expect exponential speed-ups from quantum machine learning using low-dimensional data because, in such cases, quantum analogues of classical algorithms will not provide ...
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Can quantum computing contribute to the development of artificial intelligence?

I am interested how quantum computing can contribute to the development of artificial intelligence, I did some searching, but could not find much. Does somebody have an idea (or speculations)?
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Transfer trained machine learning model

I know just the basics of quantum computer i.e. superposition, entanglement, gates and few other kinds of stuff. Now the question is it possible to transfer a trained machine learning model from IBM ...
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Distance calcluation between two vectors

In Quantum Machine Learning for data scientists, Page 34 gives an algorithm to calculate the distance between two classifical vectors. As mentioned in this question, it is not clear how the SwapTest ...
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Encoding Binary Data into Quantum Basis

I am working on implementing a paper on QNNs. I have successfully been able to resize a MNIST digit to be able to meet the size of quantum circuit. But I am not clear of how to convert the resized ...
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Quantum Optimization via Quantum Label Classification in Quantum Circuits

I have been reading Farhi and Neven's paper on quantum neural networks on quantum circuits. I also found an example - albeit not ideal as pointed out by a couple of users - thank you - in here. ...
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Reinforcement learning with a quantum agent [closed]

Is it an open question whether we can do reinforcement learning where the quantum agent is not present in the environment, that is, doesn't contribute noise to the environment? In a classical ...
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638 views

How to run quantum SVM algorithm from Qiskit in real IBM Quantum Computer using IBMQ?

I'm trying to run QSVM algorithm in IBMQ experience, want to run in one of those real quantum computers. ...
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How to plot decision boundary with support vectors when running quantum SVM algorithm?

I'm working on QSVM to know the difference between SVM and QSVM. How much better quantum machine learning can do when compared to classical machine learning algorithms? Part of my code: ...
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How to encode MNIST data set on a quantum circuit to study supervised learning with QNN?

I am trying to implement arXiv:1802.06002†. I do not understand how to take the data set from MNIST and apply it to a quantum circuit. [†]: Classification with Quantum Neural Networks on Near Term ...
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453 views

Can quantum computing speed up Bayesian learning?

One of the biggest drawbacks of Bayesian learning against deep learning is runtime: applying Bayes' theorem requires knowledge on how the data is distributed, and this usually requires either ...
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956 views

Is there any potential application of quantum computers in machine learning or AI?

A lot of people believe that quantum computers can prove to be a pivotal step in creating new machine learning and AI algorithms that can give a huge boost to the field. There have even been studies ...
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How to build a quantum circuit representing the Ising Model?

Can someone explain to me how to build a quantum circuit representing the Ising Model? I just want to understand how to represent the Ising Model for the purposes of quantum state label classification....
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3answers
322 views

Swap Test for vector difference - how are different sized inputs combined?

I'm working on a similar problem of that raised by Aman in Inner product of quantum states Concerning the use of Swap Test for calculating the difference of two vectors. An example of the original ...
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1answer
661 views

How to study quantum machine learning?

I want to make my quantum machine learning algorithms. As far as I understand I must learn: basics of quantum physics, quantum computing (and algorithms), classical machine learning, quantum ...
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506 views

Quantum machine learning after Ewin Tang

Recently, a series of research papers have been released (this, this and this, also this) that provide classical algorithms with the same runtime as quantum machine learning algorithms for the same ...
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Why does $x\sqrt{1-x^2}$ enhance the ability to approximate analytical functions in quantum circuit learning?

In this paper Quantum Circuit Learning they say that the ability of a quantum circuit to approximate a function can be enhanced by terms like $x\sqrt{1-x^2}$ ($x\in[-1,1])$. Given inputs $\{x,f(x)\}$, ...
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386 views

How to recognize if a paper is talking about quantum annealing or gate logic?

I am currently reading various survey papers in Quantum Machine Learning, such as "Quantum Machine Learning" by Biamonte, Wittek, Pancotti, Rebentrost, Wiebe, and Lloyd. To me, it is not clear when ...
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404 views

Can quantum annealing be used for training convolutional neural networks?

Simulated annealing is applied for deep learning using convolutional neural networks. Likewise, can quantum annealing be used? These two papers: Simulated Annealing Algorithm for Deep Learning (...
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Embedding classical information into norm of a quantum state

According to An introduction to quantum machine learning (Schuld, Sinayskiy & Petruccione, 2014), Seth Lloyd et al. say in their paper: Quantum algorithms for supervised and unsupervised machine ...
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1answer
440 views

Is quantum backpropagation faster than classical backpropagation?

I recently stumbled upon a press release from Xanadu.ai stating that Under the hood, PennyLane's core feature is that it implements a version of the backpropagation algorithm - the workhorse for ...
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Are there any examples of anyone applying quantum algorithms to problems in computational biology?

As the title suggests, I'm searching for published examples of quantum algorithms being applied to problems in computational biology. Clearly the odds are high that practical examples don't exist (yet)...
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What do “$i$-th basic network”, “quantum multiplexers” and “quantum parallelism” mean in this context? How are they beneficial?

I have been reading the paper A quantum-implementable neural network model (Chen et al., 2017) for a few days now, but failed to understand how exactly their algorithm offers a speedup over the ...
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1answer
141 views

Where can I find example circuits to learn from?

I'm relatively new to quantum computing and my goal is to learn how to implement algorithms that I read in papers. While I have found many circuit snippets I have yet to find a repository of examples ...
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What are some of the interesting problems whose solutions have been proposed using quantum neural networks?

I know there are some "quantum versions" of hand-writing recognition algorithms which have been proposed using quantum neural networks. Example: "Recognition of handwritten numerals by Quantum Neural ...
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Gradient boosting akin to XGBoost using a quantum device

I am currently trying to implement a boosting algorithm akin to XGBoost with a quantum device. The reason is that I want to make use of a quantum device to train weak classifiers. However, as far as I ...