Selected Papers

2022

• Saga: A Platform for Continuous Construction and Serving of Knowledge At Scale Ihab Ilyas, Theodoros Rekatsinas, Vishnu Konda, Jeffrey Pound, Xiaoguang Qi, Mohamed Soliman. SIGMOD 2022
• Marius++: Large-Scale Training of Graph Neural Networks on a Single Machine Roger Waleffe et al., In Submission
• Machine Learning and Data Cleaning: Which Serves the Other? Ihab Ilyas and Theodoros Rekatsinas Journal of Data and Information Quality 2022 (invited)
• Ember: No-Code Context Enrichment via Similarity-Based Keyless Joins Sahaana Suri et al. VLDB 2022
• Can Transfer Learning be used to build a Query Optimizer? Yunjia Zhang et al. CIDR 2022

2021

• Picket: Guarding Against Corrupted Data in Tabular Data during Learning and Inference Zifan Liu et al. VLDB Journal 21
• Demo of Marius: A System for Large-scale Graph Embeddings Anze Xie et al. VLDB demo 21
• Marius: Learning Massive Graph Embeddings on a Single Machine Jason Mohoney et al. OSDI 21
• On Robust Mean Estimation under Coordinate-level Corruption Zifan Liu et al. ICML 21

2020

• Unsupervised Relation Extraction from Language Models using Constrained Cloze Completion Ankur Goswami et al. EMNLP-Findings 20
• Data-Dependent Differentially Private Parameter Learning for Directed Graphical Models Amrita Chowdhury et al. ICML 20
• A Statistical Perspective on Discovering Functional Dependencies in Noisy Data Yunjia Zhang et al. SIGMOD 20
• Attention-based Learning For Missing Data Imputation in HoloClean Richard Wu et al. MLSys 20
• Principal Component Networks: Parameter Reduction Early in Training Roger Waleffe and Theodoros Rekatsinas Manuscript

2019

• Approximate Inference in Structured Instances with Noisy Categorical Observations Alireza Heidari et al. UAI 19
• HoloDetect: Few-Shot Learning for Error Detection Alireza Heidari et al. SIGMOD 19
• A Formal Framework For Probabilistic Unclean Databases De Sa et al. ICDT 19
• Data Integration and Machine Learning: A Natural Synergy Xin Luna Dong and Theodoros Rekatsinas VLDB, SIGMOD, KDD Tutorials 19

2018

• Deep Learning For Entity Matching: A Design Space Exploration Sidharth Mudgal et al. SIGMOD 18
• Fonduer: Knowledge Base Construction from Richly Formatted Data Sen Wu et al. SIGMOD 18

2017 and older

• HoloClean: Holistic Data Repairs with Probabilistic Inference Theodoros Rekatsinas et al. VLDB 17
• SLiMFast: Guaranteed Results for Data Fusion and Source Reliability Theodoros Rekatsinas et al. SIGMOD 17
• Forecasting Rare Disease Outbreaks from Open Source Indicators Theodoros Rekatsinas et al. Journal of Statistical Analysis and Data Mining, Best of SDM Special Issue, 2016
• SourceSight: Enabling Effective Source Selection Theodoros Rekatsinas et al. SIGMOD demo 16
• HawkesTopic: A Joint Model for Network Inference and Topic Modeling from Text-Based Cascades Xinran He, Theodoros Rekatsinas et al. ICML 15
• SourceSeer: Forecasting Rare Disease Outbreaks Using Multiple Data Sources Rekatsinas et al. SDM 15 Best Paper Award
• Finding Quality in Quantity: The Challenge of Discovering Valuable Sources for Integration Rekatsinas et al. CIDR 15
• Characterizing and selecting fresh data sources Rekatsinas et al. SIGMOD 14
• SPARSI: partitioning sensitive data amongst multiple adversaries Rekatsinas et al. VLDB 13
• Local structure and determinism in probabilistic databases Rekatsinas et al. SIGMOD 12