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Zaharah Bukhsh
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2020 – today
- 2024
- [j1]Roel Bouman, Zaharah Bukhsh, Tom Heskes:
Unsupervised Anomaly Detection Algorithms on Real-world Data: How Many Do We Need? J. Mach. Learn. Res. 25: 105:1-105:34 (2024) - [c1]Francesca Meneghello, Jeroen Middelhuis, Laura Genga, Zaharah Bukhsh, Massimiliano Ronzani, Chiara Di Francescomarino, Chiara Ghidini, Remco M. Dijkman:
Optimizing Resource Allocation Policies in Real-World Business Processes Using Hybrid Process Simulation and Deep Reinforcement Learning. BPM 2024: 167-184 - [i4]Jesse van Remmerden, Maurice Kenter, Diederik M. Roijers, Charalampos Andriotis, Yingqian Zhang, Zaharah Bukhsh:
Deep Multi-Objective Reinforcement Learning for Utility-Based Infrastructural Maintenance Optimization. CoRR abs/2406.06184 (2024) - [i3]Igor G. Smit, Jianan Zhou, Robbert Reijnen, Yaoxin Wu, Jian Chen, Cong Zhang, Zaharah Bukhsh, Wim Nuijten, Yingqian Zhang:
Graph Neural Networks for Job Shop Scheduling Problems: A Survey. CoRR abs/2406.14096 (2024) - [i2]Jesse van Remmerden, Zaharah Bukhsh, Yingqian Zhang:
Offline Reinforcement Learning for Learning to Dispatch for Job Shop Scheduling. CoRR abs/2409.10589 (2024) - 2023
- [i1]Roel Bouman, Zaharah Bukhsh, Tom Heskes:
Unsupervised anomaly detection algorithms on real-world data: how many do we need? CoRR abs/2305.00735 (2023)
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last updated on 2024-11-08 21:28 CET by the dblp team
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