6 citations · 9 across the 5 of their papers we have counts for
10 papers
Non-Negative Matrix Factorization Using Non-Von Neumann Computers
Ajinkya Borle, Charles Nicholas, Uchenna Chukwu +2
Non-negative matrix factorization (NMF) is a matrix decomposition problem with applications in unsupervised learning. The general form of this problem (along with many of its varia…
Biclustering a dataset using photonic quantum computing
Ajinkya Borle, Ameya Bhave
Biclustering is a problem in machine learning and data mining that seeks to group together rows and columns of a dataset according to certain criteria. In this work, we highlight t…
Adaptive Quantum Optimized Centroid Initialization
Nicholas R. Allgood, Ajinkya Borle, Charles K. Nicholas
Prototype-based clustering algorithms such as k-means are sensitive to the selection of initial cluster centroids, with poor initialization leading to slower convergence and subopt…
On Quantum Annealing Without a Physical Quantum Annealer
Ameya Bhave, Ajinkya Borle
Quantum annealing is an emerging metaheuristic used for solving combinatorial optimisation problems. However, hardware based physical quantum annealers are primarily limited to a s…
Quantum Optimized Centroid Initialization
Nicholas R. Allgood, Ajinkya Borle, Charles K. Nicholas
One of the major benefits of quantum computing is the potential to resolve complex computational problems faster than can be done by classical methods. There are many prototype-bas…
How viable is quantum annealing for solving linear algebra problems?
Ajinkya Borle, Samuel J. Lomonaco
With the increasing popularity of quantum computing and in particular quantum annealing, there has been growing research to evaluate the meta-heuristic for various problems in line…
Quantum Approximate Optimization for Hard Problems in Linear Algebra
Ajinkya Borle, Vincent E. Elfving, Samuel J. Lomonaco
The Quantum Approximate Optimization Algorithm (QAOA) by Farhi et al. is a quantum computational framework for solving quantum or classical optimization tasks. Here, we explore usi…
On Post-Processing the Results of Quantum Optimizers
Ajinkya Borle, Josh McCarter
The use of quantum computing for applications involving optimization has been regarded as one of the areas it may prove to be advantageous (against classical computation). To furth…
Bayesian Networks based Hybrid Quantum-Classical Machine Learning Approach to Elucidate Gene Regulatory Pathways
Radhakrishnan Balu, Ajinkya Borle
We report a scalable hybrid quantum-classical machine learning framework to build Bayesian networks (BN) that captures the conditional dependence and causal relationships of random…
Analyzing the Quantum Annealing Approach for Solving Linear Least Squares Problems
Ajinkya Borle, Samuel J. Lomonaco
With the advent of quantum computers, researchers are exploring if quantum mechanics can be leveraged to solve important problems in ways that may provide advantages not possible w…