activity
20182026
most citedVamsa: Automated Provenance Tracking in Data Science Scripts

48 citations · 113 across the 9 of their papers we have counts for

collaborators
Showing cs.DBShow all

7 papers · 1 filter

cs.DB2026

Nexus: Inferring Join Graphs from Metadata Alone via Iterative Low-Rank Matrix Completion

Tianji Cong, Yuanyuan Tian, Andreas Mueller +5

Automatically inferring join relationships is a critical task for effective data discovery, integration, querying and reuse. However, accurately and efficiently identifying these r…

cs.DB2023

Rapidash: Efficient Constraint Discovery via Rapid Verification

Zifan Liu, Shaleen Deep, Anna Fariha +3

Denial Constraint (DC) is a well-established formalism that captures a wide range of integrity constraints commonly encountered, including candidate keys, functional dependencies,…

cs.DB2022

OneProvenance: Efficient Extraction of Dynamic Coarse-Grained Provenance from Database Logs [Technical Report]

Fotis Psallidas, Ashvin Agrawal, Chandru Sugunan +6

Provenance encodes information that connects datasets, their generation workflows, and associated metadata (e.g., who or when executed a query). As such, it is instrumental for a w…

cs.DB2019★ 16 cited

Extending Relational Query Processing with ML Inference

Konstantinos Karanasos, Matteo Interlandi, Doris Xin +10

The broadening adoption of machine learning in the enterprise is increasing the pressure for strict governance and cost-effective performance, in particular for the common and cons…

cs.DB2019★ 21 cited

Cloudy with high chance of DBMS: A 10-year prediction for Enterprise-Grade ML

Ashvin Agrawal, Rony Chatterjee, Carlo Curino +19

Machine learning (ML) has proven itself in high-value web applications such as search ranking and is emerging as a powerful tool in a much broader range of enterprise scenarios inc…

cs.DB2018

Provenance for Interactive Visualizations

Fotis Psallidas, Eugene Wu

We highlight the connections between data provenance and interactive visualizations. To do so, we first incrementally add interactions to a visualization and show how these interac…

cs.DB2018★ 15 cited

Smoke: Fine-grained Lineage at Interactive Speed

Fotis Psallidas, Eugene Wu

Data lineage describes the relationship between individual input and output data items of a workflow, and has served as an integral ingredient for both traditional (e.g., debugging…