Papers accepted from the MLJ track with DSAA’2024 (https://dsaa2024.dsaa.co/cfp-mlj-journal-track.html), to be presented at DSAA’2025.
Journal Track with Machine Learning
- Ziying Li (The University of Sydney); Junbin Gao (University of Sydney, Australia)*. “Heterogeneous Graph-based Polarization Detection (HG-PD): a Model Balancing Crude Processing with Rich Semantics”
- Zhiwen Luo (Concordia University); Wentao Fan (Beijing Normal University-Hong Kong Baptist University United International College (UIC))*; Manar Amayri (Concordia university); Nizar Bouguila (Concordia University). “High-Dimensional Axial Data Clustering via Watson Mixture Variational Autoencoder”
- Junhan Wen (Delft University of Technology)*; Thomas Abeel (Delft University of Technology); Mathijs de Weerdt (Delft University of Technology). “Performance and Interaction Assessment of Neural Network Architectures and Bivariate Smart Predict-then-Optimize”
- Roohollah Roohollah (Toronto Metropolitan University); Morteza Zihayat (Toronto Metropolitan University)*; Kuan Feng (IBM Cloud Pak for Multicloud Management Development); Jason Adelman (IBM Cloud Pak for Multicloud Management Development); Fattane Zarrinkalam (University of Guelph); Ebrahim Bagheri (Ryerson University). “Jointly Learning Content-Network Representations for Collaborative Expert Discovery”
- Umer Siddique (University of Texas at San Antonio)*; Abhinav Sinha (University of Cincinnati); Yongcan Cao (University of Texas at San Antonio). “Learning Fair Policies in Multi-Objective Preference-based Reinforcement Learning”
Special track on Emerging Data Science Advances
- Samuel Stocksieker (Institut de Mathématiques de Marseille / Aix-Marseille University)*; Denys Pommeret (Institut de Mathématiques de Marseille / Aix-Marseille University / CNRS); Arthur Charpentier (UQAM). “Delving into Deep Smoothed Bootstrap: Application in Imbalanced Regression”
- Sarwan Ali (Georgia State University)*. “Murmur2Vec: A Hashing Based Approximate Solution For Embedding Generation Of COVID-19 Spike Sequences”
- Mert Cakiroglu (Indiana University); HASAN KURBAN (TEXAS A&M)*; Elham Buxton (UIS); Mehmet Dalkilic (Indiana University). “Novel De Bruijn Graph Embeddings for Enhanced Time Series Forecasting”
- Jie Ou (University of Electronic Science and Technology of China); Xiaowang Li (University of Electronic Science and Technology of China); Yueming Chen (University of Electronic Science and Technology of China); Jiahong Qian (Huawei Technologies Co. Ltd); Teng Su (Huawei Technologies Co. Ltd); Tian Wenhong (University of Electronic Science and Technology of China)*. “Efficient and Automatic 3D Parallelism Strategies Search via Contrastive Reinforcement Learning Pretrained Neural Networks”
- Seungeon Lee (DGIST); Sang-Chul Lee (DGIST)*. “TablEye: Few-shot tabular learning in the Image domain”
- Manuel Dileo (University of Milan)*; Matteo Zignani (Università degli Studi di Milano); Sabrina Gaito (Università degli Studi di Milano). “A discrete-time deep learning framework for temporal heterogeneous networks forecasting”
- Sónia Teixeira (INESC TEC)*; Rita Nogueira (INESCTEC); Joao Gama (INESC TEC – LIAAD). “Unveiling Fairness, Sustainability and Performance of Causal Discovery”