Quadratic Unconstrained Binary Optimization

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3 papers in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

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Q-DEQ: Discrete Solving and Quantization for Deep Equilibrium Models in Time Series Forecasting under Edge Deployment Coding Constraints
Sep 21, 2026Ruotong Yang, Hongdong Zhu, Qi Gao +3Forecasting Backbone Time Series Forecasting
Task-Aware QUBO Allocation for Mixed-Precision Quantization
Sep 4, 2026Osama Orabi, Artur Zagitov, Hadi Salloum +2Mixed-Precision Quantization Quadratic Unconstrained Binary Optimization
Laboratory of Quantum Computing, Innopolis University, 420500 Innopolis, Russia · Q Deep, Laboratory of Quantum Computing, 420502 Innopolis, Russia · Moscow Independent Research Institute of Artificial Intelligence (MIRAI), 117218 Moscow, Russia +2
GNN-Guided Graph Coarsening and Adaptive QUBO Penalties for the Capacitated Vehicle Routing Problem with Time Windows on a Quantum Annealer
Sep 4, 2026Youssef Kamel Rezk, Paweł GoraVehicle Routing Problem Quadratic Unconstrained Binary Optimization
Alamein International University, Alamein, Egypt · Jagiellonian University, Kraków, Poland · Fundacja Quantum AI, Warsaw, Poland
LC-Implicit-QAOA: Active-Workspace-Capped Exact Objective-and-Gradient Evaluation for Training over Bounded QUBO Light Cones
Aug 6, 2026Chih-Chung HsuQuantum Approximate Optimization Algorithm Quadratic Unconstrained Binary Optimization
Institute of Smart Industry and Green Energy, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
Superpixel-Based QUBO for Scalable Quantum-Enhanced Medical Image Segmentation
Jul 27, 2026Mohammad Chalhoub, Mahdi Chehimi, Laia Domingo +3Quadratic Unconstrained Binary Optimization Quantum Approximate Optimization Algorithm
Department of Electrical and Computer Engineering, American University of Beirut, Beirut, Lebanon · Centre de Visi´o per Computador (CVC), Barcelona, Spain · Ingenii Inc., New York, USA +3
Formulation-Level Auto-Tuning for QUBO-Based Machine Learning: A Case Study Across Multiple Quantum-Inspired Annealers
Jul 21, 2026Naoya Mizuki, Takahiro Katagiri, Daichi Mukunoki +1Quantum Annealing Quadratic Unconstrained Binary Optimization
Graduate School of Informatics, Nagoya University · Information Technology Center, Nagoya University
Quantum CT via Dynamic Interval Encoding and Prior-Balanced QUBO Reconstruction
Jun 23, 2026Ao Wang, Yikuang Yuluo, Yujie Liu +7Quadratic Unconstrained Binary Optimization Cone-Beam Computed Tomography
Stage-dependent integer-binary encoding in factorization-machine black-box optimization
Jun 22, 2026Ryo Ogawa, Mayumi Nakano, Yuya Seki +1Quadratic Unconstrained Binary Optimization Black-Box Optimization
Graduate School of Science and Technology, Keio University, Kanagawa 223-8522, Japan · Keio University Sustainable Quantum Artificial Intelligence Center (KSQAIC), Keio University, Tokyo 108-8345, Japan · Department of Applied Physics and Physico-Informatics, Keio University, Kanagawa 223-8522, Japan +2
Quantum Annealing Enhanced Reinforcement Learning for Accurate Remaining Useful Lifetime Prediction
Jun 16, 2026Manoranjan Gandhudi, Arunkumar V., G. R. Anil +1Quantum Annealing Useful Life Prediction
Central University of Karnataka, Kalaburagi, India · University College of Engineering, Anna University, Tiruchirappalli, Tamil Nadu, India · AIONOS India Pvt Ltd, Hyderabad, India +1
Optimality-Preserving Decomposition for Scalable QAOA in Natural-Language-Guided Multi-Drone Assignment
Jun 12, 2026Junyeop Bang, Byongho Lee, Dohyun An +1Quantum Approximate Optimization Algorithm Quantum Annealing
Department of Smart Convergence Korea University Republic of Korea · School of Electrical Engineering Korea University Republic of Korea
Coordinated optimization of departure sequencing and section-track allocation in railway short-term concentrated departure scenarios based on qubo and hybrid quantum algorithms
Jun 4, 2026Xiaobin Li, Yanbin Gao, Weiguang Wang +1Quadratic Unconstrained Binary Optimization Relighting
School of Transportation Engineering East China Jiaotong University Nanchang, Jiangxi 330000, China
Implicit Binarization via Complex Phase Dynamics in Combinatorial Optimization
May 23, 2026Khen Cohen, Mark Glass, Meir Feder +1Quadratic Unconstrained Binary Optimization Convex Relaxation
School of Physics and Astronomy, Tel Aviv University, Tel Aviv, Israel · School of Electrical and Computer Engineering, Tel Aviv University, Tel Aviv, Israel
Combinatorial Optimization of Robotic Hand Kinematic Structures Using a Potential-Dexterity-Based QUBO Formulation
May 15, 2026HyoJae Kang, Yeong Jae Park, Jeongdo Ahn +1Quadratic Unconstrained Binary Optimization Quantum Annealing
Advanced Robotics Research Center, Korea Institute of Machinery & Materials (KIMM) · Mechanical Engineering, University of Science & Technology (UST)
Byzantine-Resilient Federated Learning via QUBO-Based Client Selection on Quantum Annealers
May 14, 2026Andras Ferenczi, Sutapa Samanta, Dagen Wang +1Federated Learning Byzantine Attacks
American Express Co · American Express Co. · Columbia University
Improving FMQA via Initial Training Data Design Considering Marginal Bit Coverage in One-Hot Encoding
May 6, 2026Taiga Hayashi, Yuya Seki, Kotaro Terada +3Quadratic Unconstrained Binary Optimization Exploratory Factor Analysis
1Graduate School of Science and Technology, Keio University, Yokohama, Kanagawa 223-8522, Japan · 2Keio Sustainable Quantum Artificial Intelligence Center, Keio University, Minato-ku, Tokyo 108-8345, Japan · 3Quanmatic Inc., Shinjuku-ku, Tokyo 162-0042, Japan +2
Q-BIOLAT: Binary Latent Protein Fitness Landscapes for QUBO-Based Optimization
Mar 29, 2026Truong-Son HyQuadratic Unconstrained Binary Optimization Protein
Department of Computer Science, University of Alabama at Birmingham, Birmingham, Alabama, USA
QuantumQUBO Agent: Automating Quadratic Unconstrained Binary Optimization (QUBO) Formulation Generation from Natural Language
Date pendingNiloy Kumar Mondal, Md Rizwan ParvezQuadratic Unconstrained Binary Optimization Quantum Annealing
Bangladesh University of Engineering and Technology · Qatar Computing Research Institute, HBKU, Doha, Qatar.

Sep 21, 2026, cs.LGJ/K move · Enter open · S save

Q-DEQ: Discrete Solving and Quantization for Deep Equilibrium Models in Time Series Forecasting under Edge Deployment Coding Constraints

Ruotong Yang, Hongdong Zhu, Qi Gao, Yin Ma+2

Forecasting Backbone Time Series Forecasting Quadratic Unconstrained Binary Optimization Functional Code Solvers Combinatorial Optimization

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Edge deployment motivates forecasting models with compact parameter storage and low-bit representations. Deep equilibrium models (DEQs) obtain implicit depth by repeatedly applying a shared layer, reducing the parameter cost of explicit layer stacking. Their usual Anderson solver, however, searches for update coefficients in the continuous real domain. We propose Q-DEQ, which formulates local updates in DEQ forward solving as discrete optimization problems. Candidate directions are constructed from the current state and iteration history, and a local quadratic residual model is used to evaluate their combinations. Binary encoding of the direction coefficients yields a quadratic unconstrained binary optimization (QUBO) problem that can be solved by simulated annealing (SA) or a coherent Ising machine (CIM). After fixed-point solving, a re-forward pass applies W8A8 fake quantization to the shared layer's weights and activations. We evaluate Q-DEQ with an iTransformer backbone on five multivariate time series forecasting datasets. Relative MSE differences from the explicit multi-layer baseline range from

-1.16\%

+2.90\%

, with lower MSE on two datasets. DEQ parameter sharing reduces parameter counts by factors of

1.80\times

3.82\times

; combined with W8A8, static weight storage is reduced by factors of

4.3\times

12.8\times

. Local QUBO problems solved using CPU-based SA and the Kaiwu CIM physical backend produce closely matching downstream forecasts. These results establish local discrete solving as a viable component of DEQ time series forecasting and provide a route for executing fixed-point updates through different combinatorial optimization backends.

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