113 citations · 250 across the 24 of their papers we have counts for
19 papers · 1 filter
Incremental IVF Index Maintenance for Streaming Vector Search
Jason Mohoney, Anil Pacaci, Shihabur Rahman Chowdhury +7
The prevalence of vector similarity search in modern machine learning applications and the continuously changing nature of data processed by these applications necessitate efficien…
High-Throughput Vector Similarity Search in Knowledge Graphs
Jason Mohoney, Anil Pacaci, Shihabur Rahman Chowdhury +5
There is an increasing adoption of machine learning for encoding data into vectors to serve online recommendation and search use cases. As a result, recent data management systems…
Saga: A Platform for Continuous Construction and Serving of Knowledge At Scale
Ihab F. Ilyas, Theodoros Rekatsinas, Vishnu Konda +3
We introduce Saga, a next-generation knowledge construction and serving platform for powering knowledge-based applications at industrial scale. Saga follows a hybrid batch-incremen…
Ember: No-Code Context Enrichment via Similarity-Based Keyless Joins
Sahaana Suri, Ihab F. Ilyas, Christopher Ré +1
Structured data, or data that adheres to a pre-defined schema, can suffer from fragmented context: information describing a single entity can be scattered across multiple datasets…
PCOR: Private Contextual Outlier Release via Differentially Private Search
Masoumeh Shafieinejad, Florian Kerschbaum, Ihab F. Ilyas
Outlier detection plays a significant role in various real world applications such as intrusion, malfunction, and fraud detection. Traditionally, outlier detection techniques are a…
Real-Time LSM-Trees for HTAP Workloads
Hemant Saxena, Lukasz Golab, Stratos Idreos +1
Real-time analytics systems employ hybrid data layouts in which data are stored in different formats throughout their lifecycle. Recent data are stored in a row-oriented format to…
Kamino: Constraint-Aware Differentially Private Data Synthesis
Chang Ge, Shubhankar Mohapatra, Xi He +1
Organizations are increasingly relying on data to support decisions. When data contains private and sensitive information, the data owner often desires to publish a synthetic datab…
Batchwise Probabilistic Incremental Data Cleaning
Paulo H. Oliveira, Daniel S. Kaster, Caetano Traina-Jr. +1
Lack of data and data quality issues are among the main bottlenecks that prevent further artificial intelligence adoption within many organizations, pushing data scientists to spen…
Approximate Denial Constraints
Ester Livshits, Alireza Heidari, Ihab F. Ilyas +1
The problem of mining integrity constraints from data has been extensively studied over the past two decades for commonly used types of constraints including the classic Functional…
Technical Report: Optimizing Human Involvement for Entity Matching and Consolidation
Ji Sun, Dong Deng, Ihab Ilyas +5
An end-to-end data integration system requires human feedback in several phases, including collecting training data for entity matching, debugging the resulting clusters, confirmin…
HoloDetect: Few-Shot Learning for Error Detection
Alireza Heidari, Joshua McGrath, Ihab F. Ilyas +1
We introduce a few-shot learning framework for error detection. We show that data augmentation (a form of weak supervision) is key to training high-quality, ML-based error detectio…
Properties of Inconsistency Measures for Databases
Ester Livshits, Rina Kochirgan, Segev Tsur +3
How should we quantify the inconsistency of a database that violates integrity constraints? Proper measures are important for various tasks, such as progress indication and action…
Distributed Dependency Discovery
Hemant Saxena, Lukasz Golab, Ihab F. Ilyas
We analyze the problem of discovering dependencies from distributed big data. Existing (non-distributed) algorithms focus on minimizing computation by pruning the search space of p…
A Formal Framework For Probabilistic Unclean Databases
Christopher De Sa, Ihab F. Ilyas, Benny Kimelfeld +2
Most theoretical frameworks that focus on data errors and inconsistencies follow logic-based reasoning. Yet, practical data cleaning tools need to incorporate statistical reasoning…
APEx: Accuracy-Aware Differentially Private Data Exploration
Chang Ge, Xi He, Ihab F. Ilyas +1
Organizations are increasingly interested in allowing external data scientists to explore their sensitive datasets. Due to the popularity of differential privacy, data owners want…
Unsupervised String Transformation Learning for Entity Consolidation
Dong Deng, Wenbo Tao, Ziawasch Abedjan +7
Data integration has been a long-standing challenge in data management with many applications. A key step in data integration is entity consolidation. It takes a collection of clus…
HoloClean: Holistic Data Repairs with Probabilistic Inference
Theodoros Rekatsinas, Xu Chu, Ihab F. Ilyas +1
We introduce HoloClean, a framework for holistic data repairing driven by probabilistic inference. HoloClean unifies existing qualitative data repairing approaches, which rely on i…
On the Relative Trust between Inconsistent Data and Inaccurate Constraints
George Beskales, Ihab F. Ilyas, Lukasz Golab +1
Functional dependencies (FDs) specify the intended data semantics while violations of FDs indicate deviation from these semantics. In this paper, we study a data cleaning problem i…
Guided Data Repair
Mohamed Yakout, Ahmed K. Elmagarmid, Jennifer Neville +2
In this paper we present GDR, a Guided Data Repair framework that incorporates user feedback in the cleaning process to enhance and accelerate existing automatic repair techniques…