Zaharah Bukhsh

According to our database, Zaharah Bukhsh authored at least 10 papers between 2024 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Self-supervise ensemble for extreme imbalance data streams with concept drift.

Yiming Teng, Zaharah Bukhsh, Yingqian Zhang, Hang Yin

Neurocomputing, 2026

2025

Deep multi-objective reinforcement learning for utility-based infrastructural maintenance optimization.

Jesse van Remmerden, Maurice Kenter, Diederik M. Roijers, Charalampos Andriotis, Yingqian Zhang, Zaharah Bukhsh

Neural Comput. Appl., October, 2025

Generalizing Beyond Suboptimality: Offline Reinforcement Learning Learns Effective Scheduling through Random Data.

Jesse van Remmerden, Zaharah Bukhsh, Yingqian Zhang

CoRR, September, 2025

Offline reinforcement learning for learning to dispatch for job shop scheduling.

Jesse van Remmerden, Zaharah Bukhsh, Yingqian Zhang

Mach. Learn., August, 2025

Learning policies for resource allocation in business processes.

Jeroen Middelhuis, Riccardo Lo Bianco, Eliran Sherzer, Zaharah Bukhsh, Ivo Adan, Remco M. Dijkman

Inf. Syst., 2025

Graph neural networks for job shop scheduling problems: A survey.

Igor G. Smit, Jianan Zhou, Robbert Reijnen, Yaoxin Wu, Jian Chen, Cong Zhang, Zaharah Bukhsh, Yingqian Zhang, Wim Nuijten

Comput. Oper. Res., 2025

Graph-Supported Dynamic Algorithm Configuration for Multi-Objective Combinatorial Optimization.

Robbert Reijnen, Yaoxin Wu, Zaharah Bukhsh, Yingqian Zhang

Proceedings of the Forty-second International Conference on Machine Learning, 2025

A Rollout-Based Algorithm and Reward Function for Resource Allocation in Business Processes.

Jeroen Middelhuis, Zaharah Bukhsh, Ivo Adan, Remco M. Dijkman

Proceedings of the Business Process Management Forum - BPM 2025 Forum, Seville, Spain, August 31, 2025

2024

Unsupervised Anomaly Detection Algorithms on Real-world Data: How Many Do We Need?

Roel Bouman, Zaharah Bukhsh, Tom Heskes

J. Mach. Learn. Res., 2024

Optimizing Resource Allocation Policies in Real-World Business Processes Using Hybrid Process Simulation and Deep Reinforcement Learning.

Francesca Meneghello, Jeroen Middelhuis, Laura Genga, Zaharah Bukhsh, Massimiliano Ronzani, Chiara Di Francescomarino, Chiara Ghidini, Remco M. Dijkman

Proceedings of the Business Process Management - 22nd International Conference, 2024