Accepted Papers

Automated Learning of Semantic Embedding Representations for Diffusion Models

Limai Jiang and Yunpeng Cai

Convergence-Guaranteed Elastic Net Graphical Model Estimation with Applications to Anomaly Localization

Dzung Phan, Matt Menickelly, Tsuyoshi Ide and Jayant Kalagnanam

Agent Reinforcement Learning Via Coalition Labeling and Structural Entropy

Dingli Su, Hao Peng, Pu Li, Guangjie Zeng, Angsheng Li and Yicheng Pan

Differentially Private Associative Co-clustering

Elena Battaglia and Ruggero G. Pensa

Hierarchical Superpixel Segmentation via Structural Information Theory

Xie Minhui, Peng Hao, Li Pu, Zeng Guangjie, Wang Shuhai, Jia Wu, Li Peng and Philip S. Yu

Staleness-Alleviated Distributed GNN Training via Online Dynamic-Embedding Prediction

Guangji Bai, Ziyang Yu, Zheng Chai, Yue Cheng and Liang Zhao

A Look Into News Avoidance Through AWRS: An Avoidance-Aware Recommender System

Igor L.R. Azevedo, Toyotaro Suzumura and Yuichiro Yasui

AnchorDrug: A system for drug-induced gene expression prediction in new contexts through active learning

Han Meng, Ruoqiao Chen, Jiayu Zhou and Bin Chen

Evidence-Based Out-of-Distribution Detection on Multi-Label Graphs

Ruomeng Ding, Xujiang Zhao, Chen Zhao, Minglai Shao, Zhengzhang Chen and Haifeng Chen

DynHAC: Fully Dynamic Approximate Hierarchical Agglomerative Clustering

Shangdi Yu, Laxman Dhulipala, Jakub Łącki and Nikos Parotsidis

Inter-Well Active Magnetic Ranging with Temporal and Interaction Network

Zelong Hao, Haitao Zhang, Yang Che and Wang Liu Zelong Hao, Haitao Zhang, Yang Che and Wang Liu

Anomaly Detection via Graph Contrastive Learning

Emre Sefer

VisTabNet: Adapting Vision Transformers for Tabular Data

Witold Wydmański, Ulvi Movsum-Zada, Jacek Tabor and Marek Śmieja

Language Models are Explorers for Join Discovery on Data Lakes

Yaohua Wang, Bolin Ding, Rong Zhu, Haibin Wang, Zhijian Ma and Jingren Zhou

AutoSTDiff: Autoregressive Spatio-Temporal Denoising Diffusion Model for Asynchronous Trajectory Generation

Rongchao Xu, Zhiqing Hong and Guang Wang

Parameter-Efficient Interventions for Enhanced Model Merging

Marcin Osial, Daniel Marczak and Bartosz Zieliński

End-To-End Self-Tuning Self-Supervised Time Series Anomaly Detection

Boje Deforce, Meng-Chieh Lee, Bart Baesens, Estefanía Serral Asensio, Jaemin Yoo and Leman Akoglu

Unanticipated replenishment: online policy for dynamic service composition in manufacturing cloud

Yang Hu, Feng Wu, Xin Li and Yu Yang

Learning Confident Classifiers in the Presence of Label Noise

Asma Ahmed Hashmi, Aigerim Zhumabayeva, Nikita Kotelevskii, Artem Agafonov, Mohammad Yaqub, Maxim Panov and Martin Takáč

TADAM: Learning Timed Automata from Noisy Observations

Lénaïg Cornanguer and Pierre-François Gimenez

Metrics for Inter-Dataset Similarity with Example Applications in Synthetic Data and Feature Selection Evaluation

Muhammad Rajabinasab, Anton Lautrup and Arthur Zimek

AVATAR: Adversarial Autoencoders with Autoregressive Refinement for Time Series Generation

Mohammadreza Eskandarinasab, Shah Muhammad Hamdi and Soukaina Filali Boubrahimi

$\ell_{1,\infty}$-Mixed Norm Promoted Row Sparsity for Fast Online CUR Decomposition Learning in Varying Feature Spaces

Zhong Chen, Yi He, Di Wu, Wenbin Zhang and Zhiqiang Deng

Equipping Graph Autoencoders: Revisiting Masking Strategies from a Robustness Perspective

Shuhan Song, Ping Li, Ming Dun, Yuan Zhang, Huawei Cao and Xiaochun Ye

GAIM: Attacking Graph Neural Networks via Adversarial Influence Maximization

Xiaodong Yang, Xiaoting Li, Huiyuan Chen and Yiwei Cai

StarRec: A Hypergraph-based Framework with Star-Expansion for Multi-Behavior Recommendation

Wenhan Zhang, Zijian Song, Yihuan Wu, Lifang Deng, Jiandong Zhang, Kaigui Bian and Bin Cui

Accurately Estimating Unreported Infections using Information Theory

Jiaming Cui, Bijaya Adhikari, Arash Haddadan, A S M Ahsan-Ul Haque, Jilles Vreeken, Anil Vullikanti and B. Aditya Prakash

DMDHC: Discovery of Multi-Density Hierarchical Cluster Structures

Walid Durani, Dominik Mautz, Claudia Plant and Christian Böhm

MEXA-CTP: Mode Experts Cross-Attention for Clinical Trial Outcome Prediction

Yiqing Zhang, Xiaozhong Liu and Fabricio Murai

Hybrid Bayesian Optimization with DIRECT

Hongsheng Liu and Dzung Phan

REGE: A Method for Incorporating Uncertainty in Graph Embeddings

Zohair Shafi, Germans Savcisens and Tina Eliassi-Rad

Task Aware Modulation using Representation Learning: An Approach for Few Shot Learning in Environmental Systems

Arvind Renganathan, Rahul Ghosh, Ankush Khandelwal and Vipin Kumar

Beyond Models! Data Valuation and Metric Adaption for Recommendation

Renqi Jia, Xiaokun Zhang, Bowei He, Qiannan Zhu, Weitao Xu, Jiehao Chen and Chen Ma

Federated Koopman-Reservoir Learning for Large-Scale Multivariate Time-Series Anomaly Detection

Long Tan Le, Tung Anh Nguyen, Han Shu, Suranga Seneviratne, Choong Seon Hong and Nguyen Tran

CoT-Decoding: Complex Reasoning via Chain-of-Thought Decoding

Guoquan Lu, Lin Peng and Li Li

Label Shift Estimation With Incremental Prior Update

Yunrui Zhang, Gustavo Batista and Salil Kanhere

Meta-learning of Class Knowledge in Zero-shot Learning

Yuta Nambu, Masahiro Kohjima, Tomoharu Iwata and Ryuji Yamamoto

Constraint-Focused Training for Multistate Survival Analysis with Neural Networks

Ryosuke Takayama and Masanao Natsumeda

OpenFE++: Efficient Automated Feature Generation via Feature Interaction

Lei Wang, Yu Shi, Yifei Jin and Jian Li

CDSRNP: Cross-Domain Sequential Recommendation via Neural Process

Haipeng Li, Jiangxia Cao, Yiwen Gao, Yunhuai Liu and Shuchao Pang

Ranking with confidence for large scale comparison data

Filipa Valdeira and Cláudia Soares

Unveiling the Impact of Local Homophily on GNN Fairness: In-Depth Analysis and New Benchmarks

Donald Loveland and Danai Koutra

Efficient Sampling of Temporal Networks with Preserved Causality Structure

Felix Stamm, Mehdi Naima and Michael T. Schaub

CoMAL: Collaborative Multi-Agent Large Language Models for Mixed-Autonomy Traffic

Huaiyuan Yao, Longchao Da, Vishnu Nandam, Justin Turnau, Zhiwei Liu, Linsey Pang and Hua Wei

Protecting Privacy against Membership Inference Attack with LLM Fine-tuning through Flatness

Tiejin Chen, Longchao Da, Huixue Zhou, Pingzhi Li, Kaixiong Zhou, Tianlong Chen and Hua Wei

Feature Deviation Embedding Improves Graph Structure Learning for Spatial Interpolation

Chaofan Li, Till Riedel and Michael Beigl

Acceleration in Low-Rank Tensor Completion

Kai Liu

An Interpretable Measure for Quantifying Predictive Dependence between Continuous Random Variables

Renato Assuncao, Flavio Figueiredo, Francisco Tinoco-Junior, Leo Sa-Freire and Fabio Silva

Approximating splits for decision trees quickly in sparse data streams

Nikolaj Tatti

Domain-Adaptive Continual Meta-Learning for Modeling Dynamical Systems: An Application in Environmental Ecosystems

Yiming Sun, Runlong Yu, Runxue Bao, Yiqun Xie, Ye Ye and Xiaowei Jia

Domain Knowledge Augmented Contrastive Learning on Dynamic Hypergraphs for Improved Health Risk Prediction

Akash Choudhuri, Hieu Vu, Kishlay Jha and Bijaya Adhikari

Conformal Edge-Weight Prediction in Latent Space

Akash Choudhuri, Yongjian Zhong, Mehrdad Moharrami, Christine Klymko, Mark Heimann, Jayaraman Thiagarajan and Bijaya Adhikari

Defense Against Shortest Path Attacks

Benjamin Miller, Zohair Shafi, Wheeler Ruml, Yevgeniy Vorobeychik, Tina Eliassi-Rad and Scott Alfeld

Optimizing Transit Network Expansion with Gated Attentive Graph Reinforcement Learning

Fanglan Chen, Dongjie Wang, Jianfeng He, Shuo Lei and Chang-Tien Lu

Context-Aware Frequency-Embedding Networks for Spatio-Temporal Portfolio Selection

Huichou Huang, Ruirui Liu, Haoxian Liu, Johannes Ruf and Qingyao Wu

Bridging Numbers and Narratives: Enhancing Financial Market Risk Predictions through Numerical Information from Financial Documents

Yu Qin, Chengshang Zhang and Wei Xu

Spatially-Delineated Domain Adapted AI Classification: An Application for Oncology Data Majid

Farhadloo, Arun Sharma, Alexey Leontovich, Svetomir Markovic and Shashi Shekhar

Trajectory Anomaly Detection with By-Design Complementary Detectors

Shurui Cao and Leman Akoglu

FedGrAINS: Personalized SubGraph Federated Learning with AdaptIve Neighbor Sampling

Emir Ceyani, Han Xie, Baturalp Buyukates, Carl Yang and Salman Avestimehr

Multi-View Spectral Clustering for Graphs with Multiple View Structures

Yorgos Tsitsikas and Evangelos E. Papalexakis

Fine-grained Spatio-temporal Event Prediction with Self-adaptive Anchor Graph

Wang-Tao Zhou, Zhao Kang, Sicong Liu, Lizong Zhang and Ling Tian

Blue Sky: Expert-in-the-Loop Representation Learning Framework for Audio Anti-Spoofing: Multimodal, Multilingual, Multi-speaker, Multi-attack (4M ) Scenarios

Zahra Khanjani, Vandana P. Janeja, Christine Mallinson, Sanjay Purushotham

Heterogeneous Multi-Agent Framework for Dynamic Generalized Category Discovery

Fatimah Alotaibi, Adithya Kulkarni, Dawei Zhou

Blue Sky: Reducing Performance Gap between Commercial and Open-Source LLMs

Adithya Kulkarni, Mohna Chakraborty

Optimizing External and Internal Knowledge of Foundation Models for Scientific Discovery

Sikun Guo, Guangzhi Xiong, Aidong Zhang

Data mining the functional architecture of the brain’s circuitry

Adam S. Charles

Explainable AI for Real-Time Video Anomaly Anticipation

David Anastasiu

What We Talk About When We Talk About AI for Science

Runlong Yu, Yiqun Xie, Xiaowei Jia

Evaluating Time Series Models with Knowledge Discovery

Li Zhang

Better AI For Understanding Life on Earth: Predict First, Design Later

Yana Bromberg, Amarda Shehu