Research Track

Research I: Graph and networks

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

Session Chair: Kristina Lerman

• 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)

Session Chair: Alimohammad Beigi

• 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)

Session Chair: Nícolas Roque dos Santos

• 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)

Session Chair: Vagelis Papalexakis

• 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)

Session Chair: Youness Diouane

• 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)

Session Chair: Bohan Jiang

• 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)

Session Chair: Xiongxiao Xu

• 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)

Session Chair: Tahani Aladwani

• 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)

Session Chair: Lisa Singh

• 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)

Session Chair: Emily Schiller

• 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)

Session Chair: Edward Raff

• 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)

Session Chair: Hasan Kurban

• 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)

Session Chair: Duong Nguyen

• 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)

Session Chair: Kunpeng Liu

• 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
• Interpretable Deep Learning for Forecasting Online Advertising Costs: Insights from the Competitive Bidding Landscape (Special session: Learning from temporal data)
  Fynn Oldenburg, Qiwei Han, Maximilian Kaiser

* Note that the Applications Track paper "Theory-guided Data-Science for Battery Modeling: Insights from a Comparative Study" by Pawel Bielski, Nico Denner, Simon Bischof, Benedikt Rzepka and Klemens Böhm will be presented in Special session: Advancing Materials Science Through Data Science at 16:00 - 17:30, October 9, 2024 (Wednesday).

Journal Track

JDSA Special Issue

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

Session Chair: Fragkiskos Malliaros

• Leveraging Local Data Sampling Strategies to Improve Federated Learning
  Christoph Düsing, Philipp Cimiano, Benjamin Paaßen
• Utilizing Structural Metrics from Knowledge Graphs to Enhance the Robustness Quantification of Large Language Models
  Mohd Ariful Haque, Marufa Kamal, Roy George, Kishor Datta Gupta
• p-ClustVal: A Novel p-adic Approach for Enhanced Clustering and Valuation in High-Dimensional Genomics Data
  Parichit Sharma, Sarthak Mishra, Hasan Kurban, Mehmet Dalkilic
• Towards Personalized Anti-Phishing: Counterfactual Explanation Approach
  Zhengyang Fan, Wanru Li, Kathryn Laskey, Kuo-Chu Chang
• Rethinking Security: The Resilience of Shallow ML Models
  Rafael Teixeira, Mário Antunes, João Paulo Barraca, Diogo Gomes, Rui L. Aguiar
• Statistically Inspired Discrepancy Detection for Anomalous Spatio-Temporal Graphs
  Atharv Tiwari, Shreyash Chatterjee, Siddharth Padmakumar, Sushanth Nair, Bhaskarjyoti Das

MLJ Special Issue

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

Session Chair: Parichit Sharma

• Invariant Representation Learning via Decoupling Style and Spurious Features
  Ruimeng Li, Yuanhao Pu, Zhaoyi Li, Chenwang Wu, Hong Xie, Defu Lian
• A Contrastive Neural Disentanglement Approach for Query Performance Prediction
  Sara Salamat, Negar Arabzadeh, Shirin Seyedsalehi, Amin Bigdeli, Morteza Zihayat, Ebrahim Bagheri
• Inferring Individual Direct Causal Effects Under Heterogeneous Peer Influence
  Shishir Adhikari, Elena Zheleva
• Event Causality Extraction through External Event Knowledge Learning and Polyhedral Word Embedding
  Xiao Wei, Chenyang Huang, Nengjun Zhu
• Weighting Non-IID Batches for Out-of-distribution Detection
  Zhilin Zhao
• Prompt-Based Contrastive Learning to Combat the COVID-19 Infodemic
  Yue Wang, Daniel Mo
• Evaluating the Robustness of Fake News Detectors to Adversarial Attacks with Real User Comments (JDSA Special Issue)
  Annat Koren, Chandler Underwood, Edoardo Serra, Francesca Spezzano