149 citations · 199 across the 3 of their papers we have counts for
5 papers · 1 filter
Circuit-based quantum random access memory for classical data with continuous amplitudes
Tiago M. L. de Veras, Ismael C. S. de Araujo, Daniel K. Park +1
Loading data in a quantum device is required in several quantum computing applications. Without an efficient loading procedure, the cost to initialize the algorithms can dominate t…
Quantum-classical reinforcement learning for decoding noisy classical parity information
Daniel K. Park, Jonghun Park, June-Koo Kevin Rhee
Learning a hidden parity function from noisy data, known as learning parity with noise (LPN), is an example of intelligent behavior that aims to generalize a concept based on noisy…
Quantum classifier with tailored quantum kernel
Carsten Blank, Daniel K. Park, June-Koo Kevin Rhee +1
Kernel methods have a wide spectrum of applications in machine learning. Recently, a link between quantum computing and kernel theory has been formally established, opening up oppo…
Parallel quantum trajectories via forking for sampling without redundancy
Daniel K. Park, Ilya Sinayskiy, Mark Fingerhuth +2
The computational cost of preparing a quantum state can be substantial depending on the structure of data to be encoded. Many quantum algorithms require repeated sampling to find t…
Circuit-Based Quantum Random Access Memory for Classical Data
Daniel K. Park, Francesco Petruccione, June-Koo Kevin Rhee
A prerequisite for many quantum information processing tasks to truly surpass classical approaches is an efficient procedure to encode classical data in quantum superposition state…