124 citations · 203 across the 12 of their papers we have counts for
12 papers
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…
Quantum Variational Rewinding for Time Series Anomaly Detection
Jack S. Baker, Haim Horowitz, Santosh Kumar Radha +6
Electron dynamics, financial markets and nuclear fission reactors, though seemingly unrelated, all produce observable characteristics evolving with time. Within this broad scope, d…
Wasserstein Solution Quality and the Quantum Approximate Optimization Algorithm: A Portfolio Optimization Case Study
Jack S. Baker, Santosh Kumar Radha
Optimizing of a portfolio of financial assets is a critical industrial problem which can be approximately solved using algorithms suitable for quantum processing units (QPUs). We b…
Origin of ferroelectric domain wall alignment with surface trenches in ultrathin films
Jack S. Baker, David R. Bowler
Engraving trenches on the surfaces of ultrathin ferroelectric (FE) films and superlattices promises control over the orientation and direction of FE domain walls (DWs). Through exp…