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SDM 2024

A

SIAM International Conference on Data Mining

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103
accepted papers
102
authors
April 18-20, 2024
dates
USA
location

103 / 103 papers

  1. 1
    3D Molecular Geometry Analysis with 2D Graphs
    Zhao Xu
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  2. 2
    A Novel Hybrid Graph Learning Method for Inbound Parcel Volume Forecasting in Logistics System
    Lisha Ye
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  3. 3
    Active Learning for Graphs with Noisy Structures
    Hongliang Chi
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  4. 4
    Ada-VAD: Domain Adaptable Video Anomaly Detection
    Dongliang Guo
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  5. 5
    AEDFL: Efficient Asynchronous Decentralized Federated Learning with Heterogeneous Devices
    Ji Liu
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  6. 6
    An Exemplars-Based Approach for Explainable Clustering: Complexity and Efficient Approximation Algorithms
    Ian Davidson
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  7. 7
    An Image Dataset for Benchmarking Recommender Systems with Raw Pixels
    Yu Cheng
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  8. 8
    Analysis of Causal and Non-Causal Convolution Networks for Time Series Classification
    Uday Singh Saini
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  9. 9
    Automated Fusion of Multimodal Electronic Health Records for Better Medical Predictions
    Suhan Cui
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  10. 10
    Blue Sky: Multilingual, Multimodal Domain Independent Deception Detection
    Dainis Boumber
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  11. 11
    Bridging Semantics: Mobility Analytics Framework for Knowledge Transfer
    Shreya Ghosh
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  12. 12
    CAMLO: Cross-Attentive Multi-View Network for Long-Term Origin-Destination Flow Prediction
    Liang Wang
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  13. 13
    CaMU: Disentangling Causal Effects in Deep Model Unlearning
    Shaofei Shen
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  14. 14
    CausalCDR: Causal Embedding Learning for Cross-domain Recommendation
    Fengxin Li
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  15. 15
    CoLafier: Collaborative Noisy Label Purifier With Local Intrinsic Dimensionality Guidance
    Dongyu Zhang
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  16. 16
    Combining Satellite and Weather Data for Crop Type Mapping: An Inverse Modelling Approach
    Praveen Ravirathinam
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  17. 17
    COMBOOD: A Semiparametric Approach for Detecting Out-of-distribution Data for Image Classification
    Magesh Rajasekaran
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  18. 18
    Data Silences: How to Unsilence the Uncertainties in Data Science
    Michael Muller
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  19. 19
    Decentralized Stochastic Compositional Gradient Descent for AUPRC Maximization
    Hongchang Gao
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  20. 20
    Deep Efficient Private Neighbor Generation for Subgraph Federated Learning
    Ke Zhang
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  21. 21
    Denoising Long- and Short-term Interests for Sequential Recommendation
    Xinyu Zhang
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  22. 22
    Differences Between Hard and Noisy-labeled Samples: An Empirical Study
    Mahsa Forouzesh
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  23. 23
    Dimensionality-Aware Outlier Detection
    Alastair Anderberg
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  24. 24
    DimReg: Embedding Dimension Search via Regularization for Recommender Systems
    Mingjun Zhao
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  25. 25
    Disinformation Detection: An Evolving Challenge in the Age of LLMs
    Bohan Jiang
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  26. 26
    Distributed Collapsed Gibbs Sampler for Dirichlet Process Mixture Models in Federated Learning
    Reda Khoufache
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  27. 27
    Dual-disentangled Deep Multiple Clustering
    Jiawei Yao
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  28. 28
    Dual-stage Flows-based Generative Modeling for Traceable Urban Planning
    Xuanming Hu
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  29. 29
    DualToken-ViT: Position-aware Efficient Vision Transformer with Dual Token Fusion
    Zhenzhen Chu
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  30. 30
    DualVAE: Dual Disentangled Variational AutoEncoder for Recommendation
    Zhiqiang Guo
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  31. 31
    Early Multiple Temporal Patterns Based Event Prediction in Heterogeneous Multivariate Temporal Data
    Nevo Itzhak
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  32. 32
    EBV: Electronic Bee-Veterinarian for Principled Mining and Forecasting of Honeybee Time Series
    Shamima Hossain
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  33. 33
    EsaCL: An Efficient Continual Learning Algorithm
    Weijieying Ren
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  34. 34
    Exploiting Multifaceted Nature of Items and Users for Session-based Recommendation
    Tianqi Sun
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  35. 35
    Feature Interaction Aware Automated Data Representation Transformation
    Ehtesamul Azim
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  36. 36
    Feature-Engineered Random Forests
    Saket Sathe
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  37. 37
    FedDCSR: Federated Cross-domain Sequential Recommendation via Disentangled Representation Learning
    Hongyu Zhang
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  38. 38
    Foundation Models for Spatiotemporal Tasks in the Physical World
    Zhe Jiang
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  39. 39
    GE-AdvGAN: Improving the transferability of adversarial samples by gradient editing-based adversarial generative model
    Zhiyu Zhu
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  40. 40
    Genius: Subteam Replacement with Clustering-based Graph Neural Networks
    Chuxuan Hu
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  41. 41
    Geospatial Topological Relation Extraction from Text with Knowledge Augmentation
    Wei Hu
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  42. 42
    Graph Summarization for Preserving Spectral Characteristics
    Houquan Zhou
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  43. 43
    Graph-based Student Knowledge Profile for Online Intelligent Education
    Jinze Wu
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  44. 44
    H2ABM: Heterogeneous Agent-based Model on Hypergraphs to Capture Group Interactions
    Vivek Anand
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  45. 45
    HADT: Human-AI Diagnostic Team via Hierarchical Reinforcement Learning
    Xuehan Zhao
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  46. 46
    Helper Recommendation with seniority control in Online Health Community
    Junruo Gao
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  47. 47
    HyperFLoRA: Federated Learning with Instantaneous Personalization
    Qikai Lu
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  48. 48
    Identification and Uses of Deep Learning Backbones via Pattern Mining
    Michael J. Livanos
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  49. 49
    Knowledge Guided Machine Learning for Extracting, Preserving, and Adapting Physics-aware Features
    Erhu He
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  50. 50
    Label Distribution Learning-Enhanced Dual-KNN for Text Classification
    Bo Yuan
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