3 citations · 4 across the 3 of their papers we have counts for
4 papers · 1 filter
A Hybrid Quantum enabled RBM Advantage: Convolutional Autoencoders For Quantum Image Compression and Generative Learning
Jennifer Sleeman, John Dorband, Milton Halem
Understanding how the D-Wave quantum computer could be used for machine learning problems is of growing interest. Our work evaluates the feasibility of using the D-Wave as a sample…
Quantum-Assisted Greedy Algorithms
Ramin Ayanzadeh, Milton Halem, John Dorband +1
We show how to leverage quantum annealers to better select candidates in greedy algorithms. Unlike conventional greedy algorithms that employ problem-specific heuristics for making…
A Method of Finding a Lower Energy Solution to a QUBO/Ising Objective Function
John E. Dorband
A new method to find a lower energy solution to a QUBO/Ising objective function will be presented in this paper. It is applied to samples returned from the D-Wave for various examp…
Improving the Accuracy of an Adiabatic Quantum Computer
John E. Dorband
The purpose of the D-Wave adiabatic quantum computer is to find a set of qubit values that minimize its objective function. For various reasons, the set of qubit values returned by…