4.7k citations · 15k across the 81 of their papers we have counts for
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A short tutorial on Wirtinger Calculus with applications in quantum information
Kelvin Koor, Yixian Qiu, Leong Chuan Kwek +1
The optimization of system parameters is a ubiquitous problem in science and engineering. The traditional approach involves setting to zero the partial derivatives of the objective…
Quantum Algorithms for the Pathwise Lasso
Joao F. Doriguello, Debbie Lim, Chi Seng Pun +2
We present a novel quantum high-dimensional linear regression algorithm with an -penalty based on the classical LARS (Least Angle Regression) pathwise algorithm. Similarly…
Challenges and Opportunities in Quantum Optimization
Amira Abbas, Andris Ambainis, Brandon Augustino +43
Recent advances in quantum computers are demonstrating the ability to solve problems at a scale beyond brute force classical simulation. As such, a widespread interest in quantum a…
Quantum approximated cloning-assisted density matrix exponentiation
Pablo Rodriguez-Grasa, Ruben Ibarrondo, Javier Gonzalez-Conde +3
Classical information loading is an essential task for many processing quantum algorithms, constituting a cornerstone in the field of quantum machine learning. In particular, the e…
Learning Restricted Boltzmann Machines with greedy quantum search
Liming Zhao, Aman Agrawal, Patrick Rebentrost
Restricted Boltzmann Machines (RBMs) are widely used probabilistic undirected graphical models with visible and latent nodes, playing an important role in statistics and machine le…
Non-Linear Transformations of Quantum Amplitudes: Exponential Improvement, Generalization, and Applications
Arthur G. Rattew, Patrick Rebentrost
Quantum algorithms manipulate the amplitudes of quantum states to find solutions to computational problems. In this work, we present a framework for applying a general class of non…