113 citations · 397 across the 33 of their papers we have counts for
12 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…
Learning Functional Dependencies with Sparse Regression
Zhihan Guo, Theodoros Rekatsinas
We study the problem of discovering functional dependencies (FD) from a noisy dataset. We focus on FDs that correspond to statistical dependencies in a dataset and draw connections…
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…
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…
Fonduer: Knowledge Base Construction from Richly Formatted Data
Sen Wu, Luke Hsiao, Xiao Cheng +4
We focus on knowledge base construction (KBC) from richly formatted data. In contrast to KBC from text or tabular data, KBC from richly formatted data aims to extract relations con…
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…
SLiMFast: Guaranteed Results for Data Fusion and Source Reliability
Manas Joglekar, Theodoros Rekatsinas, Hector Garcia-Molina +2
We focus on data fusion, i.e., the problem of unifying conflicting data from data sources into a single representation by estimating the source accuracies. We propose SLiMFast, a f…
CrowdGather: Entity Extraction over Structured Domains
Theodoros Rekatsinas, Amol Deshpande, Aditya Parameswaran
Crowdsourced entity extraction is often used to acquire data for many applications, including recommendation systems, construction of aggregated listings and directories, and knowl…
On Sharing Private Data with Multiple Non-Colluding Adversaries
Theodoros Rekatsinas, Amol Deshpande, Ashwin Machanavajjhala
We present SPARSI, a theoretical framework for partitioning sensitive data across multiple non-colluding adversaries. Most work in privacy-aware data sharing has considered disclos…