From the 1 of 6 linked papers with an AI index.
6 papers
Hardware-Aware QUBO Reformulation of Constrained Binary Optimization via the Walsh-Fourier Transform
Loong Kuan Lee, Harsha Nagarajan, Thore Gerlach +3
The paper proposes a slack‑free, penalty‑based method that reformulates constrained binary optimization problems into QUBO form using a Walsh‑Fourier projection that respects the c…
Quadratic Continuous Quantum Optimization
Sascha Mücke, Thore Gerlach, Nico Piatkowski
Quantum annealers can solve QUBO problems efficiently but struggle with continuous optimization tasks like regression due to their discrete nature. We introduce Quadratic Continuou…
On the Impact of Weight Discretization in QUBO-Based SVM Training
Sascha Mücke
Training Support Vector Machines (SVMs) can be formulated as a QUBO problem, enabling the use of quantum annealing for model optimization. In this work, we study how the number of…
Kernel -Medoids as General Vector Quantization
Thore Gerlach, Sascha Mücke, Christian Bauckhage
Vector Quantization (VQ) is a widely used technique in machine learning and data compression, valued for its simplicity and interpretability. Among hard VQ methods, -medoids clu…
QUBOLite: A lightweigth Python toolkit for QUBO
Sascha Mücke, Thore Gerlach, Nico Piatkowski +1
We present QUBOLite, a Python package for the creation, manipulation, analysis, and solution of Quadratic Unconstrained Binary Optimization (QUBO) instances. Built as a thin wrappe…
Quantum Adiabatic Generation of Human-Like Passwords
Sascha Mücke, Raoul Heese, Thore Gerlach +3
Generative Artificial Intelligence (GenAI) for Natural Language Processing (NLP) is the predominant AI technology to date. An important perspective for Quantum Computing (QC) is th…