Research Track

Research I: Graph and networks

11:00 - 12:30, October 7, 2024 (Monday)

• Estimate and Reduce Uncertainty in Uncertain Graphs
  Naheed Anjum Arafat, Ehsan Bonabi Mobaraki, Arijit Khan, Yllka Velaj and Francesco Bonchi
• Semi-supervised Coarsening of Bipartite Graphs for Text Classification via Graph Neural Network
  Nícolas Roque dos Santos, Diego Minatel, Alan Demétrius Baria Valejo and Alneu de Andrade Lopes
• Influence Role Recognition and LLM-based Scholar Recommendation in Academic Social Networks
  Prasad Calyam, Xiyao Cheng, Mayank Kejriwal, Yuanxun Zhang and Lakshmi Srinivas Edara

Research II: Clustering

14:00 - 15:30, October 7, 2024 (Monday)

• Validating Arbitrary Shaped Clusters - A Survey
  Georg Stefan Schlake and Christian Beecks
• Using Annealing to Accelerate Triangle Inequality k-means
  Alibek Zhakubayev and Greg Hamerly
• Beta k-means: Accelerating k-means Using Probabilistic Cluster Filtering
  Alibek Zhakubayev and Greg Hamerly
• A Novel Particle Swarm Optimization Algorithm for Meta-heuristic Analysis Mechanism Based on Population Learning Strategies and Adaptive Selection of Leadership Particles
  Yuheng Wu, Xingyu Zhu, Wenxu Zhao and Xiaona Xia

Research III: Multi-modal multi-view analysis

16:00 - 17:30, October 7, 2024 (Monday)

• Diffusion Models for Cross-Domain Image-to-Image Translation with Paired and Partially Paired Datasets
  Evan Bell and Dan Li
• Beyond Simple Averaging: Improving NLP Ensemble Performance with Topological-Data-Analysis-Based Weighting
  Polina Proskura and Alexey Zaytsev
• Multi-view relational evidential c-medoid clustering with adaptive weighted
  Armel Soubeiga, Violaine Antoine and Sylvain Moreno

Research IV: Data augmentation & Self-supervised learning

11:00 - 12:30, October 8, 2024 (Tuesday)

• Masked Contrastive Representation Learning for Self-supervised Visual Pre-training
  Yuchong Yao, Nandakishor Desai and Marimuthu Palaniswami
• Efficient Data Completion and Augmentation
  Antonina Krajewska and Ewa Niewiadomska-Szynkiewicz
• CL-FML: Cluster-based & Label-aware Federated Meta-Learning for On-Demand Classification Tasks
  Tahani Aladwani, Christos Anagnostopoulos, Shameem Puthiya Parambath and Fani Deligianni

Research V: AI for health

14:00 - 15:30, October 8, 2024 (Tuesday)

• Media Bias Matters: Understanding the Impact of Politically Biased News on Vaccine Attitudes in Social Media
  Bohan Jiang, Lu Cheng, Zhen Tan, Ruocheng Guo and Huan Liu
• AI-based Mental Health Assessment for Adolescents Using Their Daily Digital Activities
  Do Hyung Kim, Joonsung Lee, Taehwi Lee, Soeun Baek, Seonghyun Jin, Haeun Yoo, Youngeun Cho, Seonghyeon Park, Kwangsu Cho and Chang-Gun Lee
• HeTAN: Heterogeneous Graph Triplet Attention Network for Drug Repurposing
  Farhan Tanvir, Khaled Mohammed Saifuddin, Tanvir Hossain, Arunkumar Bagavathi and Esra Akbas

Research VI: Online social media analysis (misinformation, hate speech)

16:00 - 17:30, October 8, 2024 (Tuesday)

• Coded Term Discovery for Online Hate Speech Detection
  Dhanush Kikkisetti, Raza Ul Mustafa, Wendy Melillo, Roberto Corizzo, Zois Boukouvalas, Jeff Gill and Nathalie Japkowicz
• Let Me Generate That for You: Generative Data Augmentation for Misinformation Detection in Low-Resource Environments
  Autumn Toney and Lisa Singh
• Model Attribution in Machine-Generated Disinformation: A Domain Generalization Approach with Supervised Contrastive Learning
  Alimohammad Beigi, Zhen Tan, Nivedh Mudiam, Canyu Chen, Kai Shu and Huan Liu

Research VII: Time series

11:00 - 12:30, October 9, 2024 (Wednesday)

• Can Large Language Models be Anomaly Detectors for Time Series?
  Sarah Alnegheimish, Linh Nguyen, Laure Berti-Equille and Kalyan Veeramachaneni
• Discovering Structural Regularities in Time Series via Gaussian Processes
  Jan David Hüwel and Christian Beecks
• Accurate estimation of cross-excitation in multivariate Hawkes process models of infectious diseases
  Youness Diouane, Frederic Schoenberg and George Mohler

Research VIII: Anomaly detection & Imbalanced learning

14:00 - 15:30, October 9, 2024 (Wednesday)

• Improving GNN-based Methods for Scam Detection in Bitcoin Transactions - A Practical Case Study
  Karanjot Saggu, Paula Branco and Guy-Vicent Jourdan
• Data Augmentation's Effect on Machine Learning Models when Learning with Imbalanced Data
  Damien Dablain and Nitesh Chawla
• MetaGAD: Meta Representation Adaptation for Few-Shot Graph Anomaly Detection
  Xiongxiao Xu, Kaize Ding, Canyu Chen and Kai Shu

Research IX: Text analytics

16:00 - 17:30, October 9, 2024 (Wednesday)

• Local Hierarchy-Aware Text-Label Association for Hierarchical Text Classification
  Ashish Kumar and Durga Toshniwal
• Deep Contrastive Active Learning for Out-of-domain Filtering in Dialog Systems
  Roland Oruche, Marcos Zampieri and Prasad Calyam
• Transparent Neighborhood Approximation for Text Classifier Explanation by Probability-based Editing
  Yi Cai, Arthur Zimek, Eirini Ntoutsi and Gerhard Wunder

Applications Track

Applications I: Health and medicine

11:00 - 12:30, October 7, 2024 (Monday)

• More Options for Prelabor Rupture of Membranes, A Bayesian Analysis
  Ashley Klein, Edward Raff, Elisabeth Seamon, Lily Foley and Timothy Bussert
• Predictive Insights into LGBTQ+ Minority Stress: A Transductive Exploration of Social Media Discourse
  Santosh Chapagain, Yuxuan Zhao, Taylor K Rohleen, Shah Muhammad Hamdi, Soukaina Filali Boubrahimi, Ryan E Flinn, Emily M Lund, Dannie Klooster, Jillian R Scheer and Cory J Cascalheira
• Few-Short Learning for Detecting Affective States from Keyboard and Mouse Data
  Ramu Gautam, Beiyu Lin and Mei Yang

Applications II: Distributed data analytics

14:00 - 15:30, October 7, 2024 (Monday)

• Using Hypervectors for Efficient Anomaly Detection in Graph Streams
  William Arliss, Andrew Godbehere and Graham Mueller
• MicroPPO: Safe Power Flow Management in Decentralized Micro-grid with Proximal Policy Optimization
  Daniel Ebi, Edouard Fouché, Marco Heyden and Klemens Böhm
• An Online Calibration Method for Robust Multi-modality 3D Object Detection
  Xingyu Li, Yige Yao, Jianming Hu and Zhidong Deng

Applications III: Business and finance

11:00 - 12:30, October 8, 2024 (Tuesday)

• Magazine supply optimization: a case-study
  Duong Nguyen, Ana Ulianovici, Sami Achour, Soline Aubry and Nicolas Chesneau
• No Data Left Behind: Exogenous Variables in Long-Term Forecasting of Nursing Staff Capacity
  Emily Schiller, Simon Müller, Kathrin Ebertsch and Jan-Philipp Steghöfer
• Alignment of Multilingual Embeddings to Estimate Job Similarities in Online Labour Market
  Simone D'Amico, Lorenzo Malandri, Fabio Mercorio, Mario Mezzanzanica and Filippo Pallucchini

Applications IV: Earth science

14:00 - 15:30, October 8, 2024 (Tuesday)

• Forecasting dissolved oxygen based on two-stage decomposition with BiLSTM-Attention and weighted Huber loss function
  Neha Pant, Durga Toshniwal and Bhola Ram Gurjar
• MIS-ME: A Multi-modal Framework for Soil Moisture Estimation
  Mohammed Rakib, Adil Aman Mohammed, Cole Diggins, Sumit Sharma, Jeff Michael Sadler, Tyson Ochsner and Arun Bagavathi
• PAW: A Deep Learning Model for Predicting Amplitude Windows in Seismic Signals
  Ariana M. Villegas Suarez, Delaine Reiter, Jonathan Rolfs and Abdullah Mueen

Applications V: Other applications

14:00 - 15:30, October 9, 2024 (Wednesday)

• Human Evaluation of ChatGPT for Scalable Python Programming Exercise Generation
  Muhammad Fawad Akbar Khan, Max Ramsdell, Hamid Karimi and Ha Nguyen
• Embedding Ordinality to Binary Loss Function for Improving Solar Flare Forecasting
  Chetraj Pandey, Anli Ji, Jinsu Hong, Rafal A. Angryk and Berkay Aydin

Special Sessions

Special session: Advancing Materials Science Through Data Science

16:00 - 17:30, October 9, 2024 (Wednesday)

• Theory-guided Data-Science for Battery Modeling: Insights from a Comparative Study (Applications Track Paper)
  Pawel Bielski, Nico Denner, Simon Bischof, Benedikt Rzepka and Klemens Böhm