125 citations · 481 across the 10 of their papers we have counts for
10 papers
Quantum Multiple Kernel Learning
Seyed Shakib Vedaie, Moslem Noori, Jaspreet S. Oberoi +2
Kernel methods play an important role in machine learning applications due to their conceptual simplicity and superior performance on numerous machine learning tasks. Expressivity…
Adiabatic Quantum Kitchen Sinks for Learning Kernels Using Randomized Features
Moslem Noori, Seyed Shakib Vedaie, Inderpreet Singh +4
Quantum information processing is likely to have far-reaching impact in the field of artificial intelligence. While the race to build an error-corrected quantum computer is ongoing…
Multi-Community Detection in Signed Graphs Using Quantum Hardware
Ehsan Zahedinejad, Daniel Crawford, Clemens Adolphs +1
Signed graphs serve as a primary tool for modelling social networks. They can represent relationships between individuals (i.e., nodes) with the use of signed edges. Finding commun…
Quantum control for high-fidelity multi-qubit gates
Raymond J. Spiteri, Marina Schmidt, Joydip Ghosh +2
Quantum control for error correction is critical for the practical use of quantum computers. We address quantum optimal control for single-shot multi-qubit gates by framing as a fe…
Combinatorial Optimization on Gate Model Quantum Computers: A Survey
Ehsan Zahedinejad, Arman Zaribafiyan
The advent of quantum computing processors with possibility to scale beyond experimental capacities magnifies the importance of studying their applications. Combinatorial optimizat…
Free energy-based reinforcement learning using a quantum processor
Anna Levit, Daniel Crawford, Navid Ghadermarzy +3
Recent theoretical and experimental results suggest the possibility of using current and near-future quantum hardware in challenging sampling tasks. In this paper, we introduce fre…