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35th SSDBM 2023: Los Angeles, CA, USA
- Robert Schuler, Carl Kesselman, Kyle Chard, Alejandro Bugacov:
Proceedings of the 35th International Conference on Scientific and Statistical Database Management, SSDBM 2023, Los Angeles, CA, USA, July 10-12, 2023. ACM 2023 - Mikayla Biggs, Yaohua Wang, Neetu Soni, Sarv Priya, Girish Bathla, Guadalupe Canahuate:
Evaluating Autoencoders for Dimensionality Reduction of MRI-derived Radiomics and Classification of Malignant Brain Tumors. 1:1-1:11 - Ivan Carvalho, Ramon Lawrence:
LearnedSort as a learning-augmented SampleSort: Analysis and Parallelization. 2:1-2:9 - Matteo Ceccarello, Anton Dignös, Johann Gamper, Christina Khnaisser:
Indexing Temporal Relations for Range-Duration Queries. 3:1-3:12 - Chenglin Zeng, Chuan Hu, Huajin Wang, Zhihong Shen:
SciDG: Benchmarking Scientific Dynamic Graph Queries. 4:1-4:12 - Joshua Chung, Marcos López de Prado, Horst D. Simon, Kesheng Wu:
Data Driven Dimensionality Reduction to Improve Modeling Performance✱. 5:1-5:16 - Alfredo Cuzzocrea:
Privacy-Preserving OLAP via Modeling and Analysis of Query Workloads: Innovative Theories and Theorems. 6:1-6:12 - Yuzhou Fang, Liang Cai, Weiwei Qiu, Fanglei Huang, Huaihai Hui:
ESM2-Tree: An maintenance efficient authentication data structure in blockchain. 7:1-7:12 - Pitikorn Khlaisamniang, Suronapee Phoomvuthisarn:
ST-CopulaGNN : A Multi-View Spatio-Temporal Graph Neural Network for Traffic Forecasting. 8:1-8:12 - Shota Suzuki, Rage Uday Kiran:
Towards Efficient Discovery of Spatially Interesting Patterns in Geo-referenced Sequential Databases. 9:1-9:11 - Fu Lin, Haonan Gong, Mingkang Li, Zitong Wang, Yue Zhang, Xuexiong Luo:
Multi-representations Space Separation based Graph-level Anomaly-aware Detection. 10:1-10:11 - Julien Mirval, Luc Bouganim, Iulian Sandu Popa:
Federated Learning on Personal Data Management Systems: Decentralized and Reliable Secure Aggregation Protocols. 11:1-11:12 - Abdulrahman Salama, Mahmoud Elkamhawy, Mohamed Ali, Eyhab Al-Masri, Adel Sabour, Abdeltawab M. Hendawi, Ming Tan, Vashutosh Agrawal, Ravi Prakash:
A Computer Vision Approach for Detecting Discrepancies in Map Textual Labels. 12:1-12:9 - Wenbo Sun, Asterios Katsifodimos, Rihan Hai:
Accelerating Machine Learning Queries with Linear Algebra Query Processing. 13:1-13:12 - Yang Wang, Xu Chen, Yang Shu Wang, Jun Yong Jing:
A Long-term Time Series Forecasting method with Multiple Decomposition. 14:1-14:9 - Bingbing Xie, Xiaoxiao Ma, Jia Wu, Jian Yang, Shan Xue, Hao Fan:
Heterogeneous Graph Neural Network via Knowledge Relations for Fake News Detection. 15:1-15:11 - Xin Zhang, Ahmed Eldawy:
Less is More: How Fewer Results Improve Progressive Join Query Processing. 16:1-16:12 - Daichi Amagata, Alejandro Ramos, Ryo Shirai, Takahiro Hara:
Fast Algorithm for Embedded Order Dependency Validation. 17:1-17:4 - Yili Wang, Jiamin Chen, Qiutong Li, Changlong He, Jianliang Gao:
MSLS: Meta-graph Search with Learnable Supernet for Heterogeneous Graph Neural Networks. 18:1-18:4 - Armin Esmaeilzadeh, Lukasz Golab, Kazem Taghva:
InfoMoD: Information-theoretic Model Diagnostics. 19:1-19:4 - Jianliang Gao, Changlong He, Jiamin Chen, Qiutong Li, Yili Wang:
Decoupled Graph Neural Architecture Search with Variable Propagation Operation and Appropriate Depth. 20:1-20:4 - Athanasios Georgoutsos, Paraskevas Kerasiotis, Verena Kantere:
Early ICU Mortality Prediction with Deep Federated Learning: A Real-World Scenario. 21:1-21:4 - Lixi Zhou, Lei Yu, Jia Zou, Hong Min:
Privacy-Preserving Redaction of Diagnosis Data through Source Code Analysis. 22:1-22:4 - Quan Wan, Shuo Yin, Xiangyue Liu, Jianliang Gao, Yuhui Zhong:
TGSLN : Time-aware Graph Structure Learning Network for Multi-variates Stock Sector Ranking Recommendation. 23:1-23:4 - Jonathan Will, Lauritz Thamsen, Dominik Scheinert, Odej Kao:
Selecting Efficient Cluster Resources for Data Analytics: When and How to Allocate for In-Memory Processing? 24:1-24:4 - Michael Behringer, Pascal Hirmer:
Interactive Data Mashups for User-Centric Data Analysis. 25:1-25:4 - Andreas Hackl, Jürgen Zeindl, Lisa Ehrlinger:
Four Factors Affecting Missing Data Imputation. 26:1-26:2
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