124 citations · 203 across the 12 of their papers we have counts for
3 papers · 1 filter
Quantum-Classical Multiple Kernel Learning
Ara Ghukasyan, Jack S. Baker, Oktay Goktas +2
As quantum computers become increasingly practical, so does the prospect of using quantum computation to improve upon traditional algorithms. Kernel methods in machine learning is…
Parallel hybrid quantum-classical machine learning for kernelized time-series classification
Jack S. Baker, Gilchan Park, Kwangmin Yu +3
Supervised time-series classification garners widespread interest because of its applicability throughout a broad application domain including finance, astronomy, biosensors, and m…
A Quantum-Inspired Binary Optimization Algorithm for Representative Selection
Anna G. Hughes, Jack S. Baker, Santosh Kumar Radha
Advancements in quantum computing are fuelling emerging applications across disciplines, including finance, where quantum and quantum-inspired algorithms can now make market predic…