3 papers
quant-ph2025
Evaluating the Quantum Approximate Optimization Algorithms for QUBO problems Across Quantum Hardware Platforms: Performance Analysis, Challenges, and Strategies
Teemu Pihkakoski, Aravind Plathanam Babu, Pauli Taipale +2
Quantum computers are expected to offer advantages in solving optimization problems challenging for classical computers. Quadratic Unconstrained Binary Optimization (QUBO) problems…
quant-ph2025
Towards reliable quantum software, algorithm and use-case development: Multidisciplinary analysis from the perspective of Finnish industries
Matti Silveri, Tommi Mikkonen, Kimmo Halunen +6
Quantum computing is a disruptive technology with the potential to transform various fields. It has predicted abilities to solve complex computational problems beyond the reach of…
cs.LG2019
Scalable K-Medoids via True Error Bound and Familywise Bandits
Aravindakshan Babu, Saurabh Agarwal, Sudarshan Babu +1
K-Medoids(KM) is a standard clustering method, used extensively on semi-metric data.Error analyses of KM have traditionally used an in-sample notion of error,which can be far from…