21 citations · 23 across the 10 of their papers we have counts for
10 papers
Certified decoding of quantum LDPC codes
Ragavi Krishnamoorthy, Florian Gerhardt, Johannes Knaute +8
Quantum low-density parity-check (qLDPC) codes reduce the qubit overhead of fault-tolerant quantum computation by an order of magnitude, but their decoding is harder than its class…
High-Order Markov Blanket Discovery via a k-Order Relaxation of the Faithfulness Assumption
Loong Kuan Lee, Ragavi Krishnamoorthy, Nico Piatkowski
The problem of learning the graphical Markov blanket (MB) of a variable from data has applications in many areas such as structure learning for Bayesian networks and Markov random…
Hardware-Aware QUBO Reformulation of Constrained Binary Optimization via the Walsh-Fourier Transform
Loong Kuan Lee, Harsha Nagarajan, Thore Gerlach +3
We present a novel slack-free, penalty-based framework for reformulating constrained binary optimization as Quadratic Unconstrained Binary Optimization (QUBO) on near-term quantum…
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…
Standardization of Multi-Objective QUBOs
Loong Kuan Lee, Thore Gerlach, Nico Piatkowski
Multi-objective optimization involving Quadratic Unconstrained Binary Optimization (QUBO) problems arises in various domains. A fundamental challenge in this context is the effecti…
Hybrid Quantum-Classical Multi-Agent Pathfinding
Thore Gerlach, Loong Kuan Lee, Frédéric Barbaresco +1
Multi-Agent Path Finding (MAPF) focuses on determining conflict-free paths for multiple agents navigating through a shared space to reach specified goal locations. This problem bec…
Multi-Objective Quantum Power System Redispatch
Loong Kuan Lee, Johannes Knaute, Florian Gerhardt +4
The rising energy production costs and the increasing reliance on volatile renewable sources have driven the need for more efficient power system redispatch strategies. In this wor…
Computing Marginal and Conditional Divergences between Decomposable Models with Applications
Loong Kuan Lee, Geoffrey I. Webb, Daniel F. Schmidt +1
The ability to compute the exact divergence between two high-dimensional distributions is useful in many applications but doing so naively is intractable. Computing the alpha-beta…
Computing Divergences between Discrete Decomposable Models
Loong Kuan Lee, Nico Piatkowski, François Petitjean +1
There are many applications that benefit from computing the exact divergence between 2 discrete probability measures, including machine learning. Unfortunately, in the absence of a…
Understanding Concept Drift
Geoffrey I. Webb, Loong Kuan Lee, François Petitjean +1
Concept drift is a major issue that greatly affects the accuracy and reliability of many real-world applications of machine learning. We argue that to tackle concept drift it is im…