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ORCID17th LION 2023: Nice, France
- Meinolf Sellmann, Kevin Tierney
:
Learning and Intelligent Optimization - 17th International Conference, LION 17, Nice, France, June 4-8, 2023, Revised Selected Papers. Lecture Notes in Computer Science 14286, Springer 2023, ISBN 978-3-031-44504-0 - Uphar Singh, Deepak Gajjala, Rahamatullah Khondoker, Harshit Gupta, Ayush Sinha, O. P. Vyas:
Anomaly Classification to Enable Self-healing in Cyber Physical Systems Using Process Mining. 1-15 - Georgios I. Liapis, Lazaros G. Papageorgiou:
Hyper-box Classification Model Using Mathematical Programming. 16-30 - Andrea Ponti, Ilaria Giordani, Antonio Candelieri, Francesco Archetti:
A Leak Localization Algorithm in Water Distribution Networks Using Probabilistic Leak Representation and Optimal Transport Distance. 31-45 - Konstantinos I. Chatzilygeroudis, Michael N. Vrahatis:
Fast and Robust Constrained Optimization via Evolutionary and Quadratic Programming. 46-61 - Kunal Jain, Prabuchandran K. J., Tejas Bodas:
Bayesian Optimization for Function Compositions with Applications to Dynamic Pricing. 62-77 - Sasan Amini, Inneke Van Nieuwenhuyse:
A Bayesian Optimization Algorithm for Constrained Simulation Optimization Problems with Heteroscedastic Noise. 78-91 - Hongbin Zhu, Yuxiao Xia, Yunzhao Li, Wei Li, Kang Liu, Xianzhou Gao:
Hierarchical Machine Unlearning. 92-106 - Zahra Parham, Vi Tching de Lille, Quentin Cappart:
Explaining the Behavior of Reinforcement Learning Agents Using Association Rules. 107-120 - Richárd Rádli, László Czúni:
Deep Randomized Networks for Fast Learning. 121-134 - Antonio Candelieri, Andrea Ponti, Francesco Archetti:
Generative Models via Optimal Transport and Gaussian Processes. 135-149 - Franck Lefebure, Cecile Thuault, Stéphane Cholet:
Real-World Streaming Process Discovery from Low-Level Event Data. 150-164 - Elisa Negrini, Giovanna Citti, Luca Capogna:
Robust Neural Network Approach to System Identification in the High-Noise Regime. 165-178 - Lilian Buzer, Tristan Cazenave:
GPU for Monte Carlo Search. 179-193 - Julien Sentuc, Farah Ellouze, Jean-Yves Lucas, Tristan Cazenave:
Learning the Bias Weights for Generalized Nested Rollout Policy Adaptation. 194-207 - Hugues Juillé, Renaud Dumeur, Paul Shaw:
Heuristics Selection with ML in CP Optimizer. 208-222 - Shudian Zhao, Calvin Tsay, Jan Kronqvist:
Model-Based Feature Selection for Neural Networks: A Mixed-Integer Programming Approach. 223-238 - Antoine Bugnicourt, Riad Mokadem, Franck Morvan, Nadia Bebeshina:
An Error-Based Measure for Concept Drift Detection and Characterization. 239-253 - Michael Römer, Felix Hagemann, Till Frederik Porrmann:
Predict, Tune and Optimize for Data-Driven Shift Scheduling with Uncertain Demands. 254-269 - Aleksandra Petrova, Javier Larrosa:
On Learning When to Decompose Graphical Models. 270-285 - Kazem Meidani, Igor Borovikov, Amir Barati Farimani, Harold Chaput:
Inverse Lighting with Differentiable Physically-Based Model. 286-300 - Augustin Parjadis, Quentin Cappart, Quentin Massoteau, Louis-Martin Rousseau:
Repositioning Fleet Vehicles: A Learning Pipeline. 301-317 - Efthyvoulos Drousiotis, Alexander M. Phillips, Paul G. Spirakis, Simon Maskell:
Bayesian Decision Trees Inspired from Evolutionary Algorithms. 318-331 - Hui Wang, Abdallah Saffidine, Tristan Cazenave:
Towards Tackling MaxSAT by Combining Nested Monte Carlo with Local Search. 332-346 - Amirreza Farahani, M. A. H. van Elzakker, Laura Genga, Pavel Troubil, Remco M. Dijkman:
Relational Graph Attention-Based Deep Reinforcement Learning: An Application to Flexible Job Shop Scheduling with Sequence-Dependent Setup Times. 347-362 - Aymen Gannouni, Luis Felipe Casas Murillo, Marco Kemmerling, Anas Abdelrazeq, Robert H. Schmitt:
Experimental Digital Twin for Job Shops with Transportation Agents. 363-377 - James Fitzpatrick, Deepak Ajwani, Paula Carroll:
Learning to Prune Electric Vehicle Routing Problems. 378-392 - Raka Jovanovic, Sertac Bayhan, Stefan Voß:
Matheuristic Fixed Set Search Applied to Electric Bus Fleet Scheduling. 393-407 - Mohit Malu, Giulia Pedrielli, Gautam Dasarathy, Andreas Spanias:
Class GP: Gaussian Process Modeling for Heterogeneous Functions. 408-423 - Melinda Thielbar, Serdar Kadioglu, Chenhui Zhang, Rick Pack, Lukas Dannull:
Surrogate Membership for Inferred Metrics in Fairness Evaluation. 424-442 - Ambrogio Maria Bernardelli, Stefano Gualandi, Hoong Chuin Lau, Simone Milanesi:
The BeMi Stardust: A Structured Ensemble of Binarized Neural Networks. 443-458 - Britt Lukassen, Laura Genga, Yingqian Zhang:
Discovering Explicit Scale-Up Criteria in Crisis Response with Decision Mining. 459-474 - Giovanni Bonetta, Davide Zago, Rossella Cancelliere, Andrea Grosso:
Job Shop Scheduling via Deep Reinforcement Learning: A Sequence to Sequence Approach. 475-490 - George Watkins, Giovanni Montana, Jürgen Branke:
Generating a Graph Colouring Heuristic with Deep Q-Learning and Graph Neural Networks. 491-505 - Bo Tang, Elias B. Khalil:
Multi-task Predict-then-Optimize. 506-522 - Hernán Ceferino Vázquez, Jorge Sanchez, Rafael Carrascosa:
Integrating Hyperparameter Search into Model-Free AutoML with Context-Free Grammars. 523-536 - Thi Quynh Trang Vo, Mourad Baïou, Viet Hung Nguyen, Paul Weng:
Improving Subtour Elimination Constraint Generation in Branch-and-Cut Algorithms for the TSP with Machine Learning. 537-551 - Marc-André Ménard, Michael Morin, Mohammed Khachan, Jonathan Gaudreault, Claude-Guy Quimper:
Learn, Compare, Search: One Sawmill's Search for the Best Cutting Patterns Across and/or Trees. 552-566 - Songhan Wong, Waldy Joe, Hoong Chuin Lau:
Dynamic Police Patrol Scheduling with Multi-Agent Reinforcement Learning. 567-582 - Lars Nagel, Nikolay Popov, Tim Süß, Ze Wang:
Analysis of Heuristics for Vector Scheduling and Vector Bin Packing. 583-598 - Yoichiro Iida, Tomohiro Sonobe, Mary Inaba:
Unleashing the Potential of Restart by Detecting the Search Stagnation. 599-613
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