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ORCID9th LOD 2023, Grasmere, UK - Part II
- Giuseppe Nicosia
, Varun Ojha, Emanuele La Malfa, Gabriele La Malfa, Panos M. Pardalos, Renato Umeton:
Machine Learning, Optimization, and Data Science - 9th International Conference, LOD 2023, Grasmere, UK, September 22-26, 2023, Revised Selected Papers, Part II. Lecture Notes in Computer Science 14506, Springer 2024, ISBN 978-3-031-53965-7
Machine Learning, Optimization, and Data Science (LOD 2023)
- Jiye Li, Yun Yin, Daniel Lafond, Alireza Ghasemi, Claver Diallo, Eric Bertrand:
Integrated Human-AI Forecasting for Preventive Maintenance Task Duration Estimation. 3-18 - Silvia Arellano, Beatriz Otero, Rubén Tous:
Exploring Image Transformations with Diffusion Models: A Survey of Applications and Implementation Code. 19-33 - Erdem Ünal, Ugur Aydin, Murat Koras, Baris Akgün, Mehmet Gönen:
Geolocation Risk Scores for Credit Scoring Models. 34-44 - Zijun Liu, Xinxin Wu, Wei Yao:
Social Media Analysis: The Relationship Between Private Investors and Stock Price. 45-54 - Leonid Sheremetov, Luis A. Lopez-Peña, Gabriela Berenice Díaz-Cortés, Dennys A. Lopez-Falcon, Erick E. Luna-Rojero:
Deep Learning Model of Two-Phase Fluid Transport Through Fractured Media: A Real-World Case Study. 55-68 - Kevin Bui, Fanghui Xue, Fredrick Park, Yingyong Qi, Jack Xin:
A Proximal Algorithm for Network Slimming. 69-83 - Gabriel Turinici:
Diversity in Deep Generative Models and Generative AI. 84-93 - Piotr Pomorski, Denise Gorse:
Improving Portfolio Performance Using a Novel Method for Predicting Financial Regimes. 94-108 - Raphael C. Engelhardt, Ralitsa Raycheva, Moritz Lange, Laurenz Wiskott, Wolfgang Konen:
Ökolopoly: Case Study on Large Action Spaces in Reinforcement Learning. 109-123 - Jan Kronqvist, Boda Li, Jan Rolfes, Shudian Zhao:
Alternating Mixed-Integer Programming and Neural Network Training for Approximating Stochastic Two-Stage Problems. 124-139 - Zoltán Tasnádi, Noémi Gaskó:
Heaviest and Densest Subgraph Computation for Binary Classification. A Case Study. 140-148 - Tarek Salhi, John R. Woodward:
SMBOX: A Scalable and Efficient Method for Sequential Model-Based Parameter Optimization. 149-162 - Taehwan Yun, Myung Jun Kim, Hyunjung Shin:
Accelerated Graph Integration with Approximation of Combining Parameters. 163-176 - Moritz Lange, Noah Krystiniak, Raphael C. Engelhardt, Wolfgang Konen, Laurenz Wiskott:
Improving Reinforcement Learning Efficiency with Auxiliary Tasks in Non-visual Environments: A Comparison. 177-191 - Punit Kumar Chaubey, Shyam Sundar:
A Hybrid Steady-State Genetic Algorithm for the Minimum Conflict Spanning Tree Problem. 192-205 - Sara Ceschia, Luca Di Gaspero, Roberto Maria Rosati, Andrea Schaerf:
Reinforcement Learning for Multi-Neighborhood Local Search in Combinatorial Optimization. 206-221 - Sven Beckmann, Bernhard Bauer:
Evaluation of Selected Autoencoders in the Context of End-User Experience Management. 222-236 - David Heik, Fouad Bahrpeyma, Dirk Reichelt:
Application of Multi-agent Reinforcement Learning to the Dynamic Scheduling Problem in Manufacturing Systems. 237-254 - Steven D. Prestwich:
Solving Mixed Influence Diagrams by Reinforcement Learning. 255-269 - Jong Ho Jhee, Jeongheun Yeon, Yoonshin Kwak, Hyunjung Shin:
Multi-scale Heat Kernel Graph Network for Graph Classification. 270-282 - Bruce Kwong-Bun Tong, Wing Cheong Lau, Chi Wan Sung, Wing Shing Wong:
PROS-C: Accelerating Random Orthogonal Search for Global Optimization Using Crossover. 283-298 - Renato De Leone, Francesca Maggioni, Andrea Spinelli:
A Multiclass Robust Twin Parametric Margin Support Vector Machine with an Application to Vehicles Emissions. 299-310 - Maria Elena Bruni, Guido Perboli, Filippo Velardocchia:
LSTM Noise Robustness: A Case Study for Heavy Vehicles. 311-323 - Panagiotis Anagnostou, Nicos G. Pavlidis, Sotiris K. Tasoulis:
Ensemble Clustering for Boundary Detection in High-Dimensional Data. 324-333 - Michael Mittermaier, Takfarinas Saber, Goetz Botterweck:
Learning Graph Configuration Spaces with Graph Embedding in Engineering Domains. 334-348
Artificial Intelligence and Neuroscience (ACAIN 2023)
- Sruthi Srinivasan, Emilia Butters, Flavia Mancini, Gemma Bale:
Towards an Interpretable Functional Image-Based Classifier: Dimensionality Reduction of High-Density Diffuse Optical Tomography Data. 351-357 - Niall McGuire, Yashar Moshfeghi:
On Ensemble Learning for Mental Workload Classification. 358-372 - Andrea Martin, Kristen Brent Venable:
Decision-Making over Compact Preference Structures. 373-387 - Habtom Kahsay Gidey, Peter Hillmann, Andreas Karcher, Alois Knoll:
User-Like Bots for Cognitive Automation: A Survey. 388-402 - Kunjira Kingphai, Yashar Moshfeghi:
On Channel Selection for EEG-Based Mental Workload Classification. 403-417 - Niall McGuire, Yashar Moshfeghi:
What Song Am I Thinking Of? 418-432 - José Diogo Marques dos Santos, José Paulo Marques dos Santos:
Path-Weights and Layer-Wise Relevance Propagation for Explainability of ANNs with fMRI Data. 433-448 - Akhila Atmakuru, Giuseppe Di Fatta, Giuseppe Nicosia, Ali Varzandian, Atta Badii:
Sensitivity Analysis for Feature Importance in Predicting Alzheimer's Disease. 449-465 - Gerard Rinkus:
A Radically New Theory of How the Brain Represents and Computes with Probabilities. 466-480
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