# Quantum Relief algorithm

@article{Liu2018QuantumRA, title={Quantum Relief algorithm}, author={Wenjie Liu and Peipei Gao and Wenbin Yu and Zhiguo Qu and Ching-Nung Yang}, journal={Quantum Information Processing}, year={2018}, volume={17}, pages={1-15} }

Relief algorithm is a feature selection algorithm used in binary classification proposed by Kira and Rendell, and its computational complexity remarkably increases with both the scale of samples and the number of features. In order to reduce the complexity, a quantum feature selection algorithm based on Relief algorithm, also called quantum Relief algorithm, is proposed. In the algorithm, all features of each sample are superposed by a certain quantum state through the CMP and rotation…

## Figures and Tables from this paper

## 25 Citations

A Quantum Feature Selection Algorithm for Multi-Classification Problem

- Computer Science2019 International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData)
- 2019

This paper proposes a quantum-based feature selection algorithm for the multi-classification problem, also called QReliefF algorithm, which is better than the classical ReliefF algorithm in efficiency and resource consumption.

Quantum-Based Feature Selection for Multiclassification Problem in Complex Systems with Edge Computing

- Computer ScienceComplex.
- 2020

A quantum-based feature selection algorithm for the multiclassification problem, namely, QReliefF, is proposed, which can effectively reduce the complexity of algorithm and improve its computational efficiency.

A Unitary Weights Based One-Iteration Quantum Perceptron Algorithm for Non-Ideal Training Sets

- Computer ScienceIEEE Access
- 2019

A novel efficient quantum perceptron algorithm based on unitary weights is proposed, where the singular value decomposition of the total weight matrix from the training set is calculated to make the weight matrix to be unitary.

Quantum Algorithms and Experiment Implementations Based on IBM Q

- Computer Science
- 2020

Three representative quantum algorithms, namely Deutsch-Jozsa, Grover, and Shor algorithms, are briefly depicted, and then their implementation circuits are presented, respectively, to show the feasibility of these algorithms and evaluate the functionality of these devices.

A unitary operator construction solution based on Pauli group for maximal dense coding with a class of symmetric states

- Computer ScienceQuantum Inf. Process.
- 2020

A feasible solution of constructing unitary operator sets for quantum maximal dense coding is proposed, which aims to use minimum qubits to maximally encode a class of t -qubit symmetric states.

Quantum Image Steganography Protocol Based on Quantum Image Expansion and Grover Search Algorithm

- Computer ScienceIEEE Access
- 2019

A large payload quantum image steganography protocol based on quantum image expansion and the Grover search algorithm and the new algorithm can not only achieve good imperceptibility and security but also large payload due to the algorithm’s good coding scalability.

A relative uncertainty measure for fuzzy rough feature selection

- Computer ScienceInt. J. Approx. Reason.
- 2021

An Extended Approach for Generating Unitary Matrices for Quantum Circuits

- Computer Science
- 2020

This paper proposes an algorithm for computing the circuit unitary matrices in detail and applies it to different reversible benchmark circuits based on NCT library and generalized Toffoli (GT) library and provides experimental results.

Quantum Solution for the 3-SAT Problem Based on IBM Q

- Computer Science
- 2019

A quantum solution for the 3-SAT problem, which includes three steps: constructing the initial state, computing the unitary \(U_f\) implementing the black-box function f and performing the inversion about the average.

A quantum key distribution scheme based on quantum error-avoiding code in decoherence-free subspace

- Physics, Computer ScienceACM TUR-C
- 2019

The proposed method of constructing a QKD scheme for quantum secure communication skillfully utilizes DFS for analysis and research, and improves the quantum bit efficiency and security of quantum key distribution.

## References

SHOWING 1-10 OF 26 REFERENCES

Training a Large Scale Classifier with the Quantum Adiabatic Algorithm

- Computer ScienceArXiv
- 2009

This communication generalizes the baseline method to large scale classifier training and provides theoretical arguments as to why the proposed optimization method is superior to versions of boosting that only minimize the empirical loss.

Quantum algorithms for nearest-neighbor methods for supervised and unsupervised learning

- Computer ScienceQuantum Inf. Comput.
- 2015

This work presents quantum algorithms for performing nearest-neighbor learning and k-means clustering and proves upper bounds on the number of queries to the input data required to compute such distances and find the nearest vector to a given test example.

A fast quantum mechanical algorithm for database search

- Computer ScienceSTOC '96
- 1996

In early 1994, it was demonstrated that a quantum mechanical computer could efficiently solve a well-known problem for which there was no known efficient algorithm using classical computers, i.e. testing whether or not a given integer, N, is prime, in a time which is a finite power of o (logN) .

Quantum adiabatic machine learning

- Computer Science, PhysicsQuantum Inf. Process.
- 2013

This work applies and illustrates this approach to machine learning and anomaly detection via quantum adiabatic evolution in detail to the problem of software verification and validation, with a specific example of the learning phase applied to a problem of interest in flight control systems.

Computational Methods of Feature Selection

- Computer Science
- 2007

This book discusses Supervised, Unsupervised, and Semi-Supervised Feature Selection Key Contributions and Organization of the Book Looking Ahead Unsuper supervised Feature Selection.

Overcoming the Myopia of Inductive Learning Algorithms with RELIEFF

- Computer ScienceApplied Intelligence
- 2004

This work reimplemented Assistant, a system for top down induction of decision trees, using RELIEFF, an extension of RELIEF, as an estimator of attributes at each selection step for heuristic guidance of inductive learning algorithms.

Equivalences and Separations Between Quantum and Classical Learnability

- Computer ScienceSIAM J. Comput.
- 2004

These results contrast known results that show that testing black-box functions for various properties, as opposed to learning, can require exponentially more classical queries than quantum queries.

Polynomial-Time Algorithms for Prime Factorization and Discrete Logarithms on a Quantum Computer

- Computer Science
- 1999

Efficient randomized algorithms are given for factoring integers and finding discrete logarithms, two problems that are generally thought to be hard on classical computers and that have been used as the basis of several proposed cryptosystems.