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Author

Divesh Srivastava

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Jul 2026

PipeLens: Identifying Interventions for Resolving Malfunctioning Data Science Pipelines

The objective is to resolve malfunctioning pipelines and improve their utility; PipeLens is introduced, a framework that leverages successful and unsuccessful runs of past pipelines for fixing pipeline malfunctions and provides causally verified root causes and suggestions that rectify malfunctions.

Jahid Hasan, Stanley Jiang, T. Singh et al. · 0 citations
Open access Aug 2026

PrivMDC: leveraging multi-dimensional correlations to answer differentially private range queries

This work proposes a new approach to answer multi-dimensional range queries that leverages multi-dimensional correlations and workload characteristics to selectively choose the data that is collected under the LDP model and proposes a new optimization step that makes use of available workload characteristics to identif...

José S. Costa, Felipe T. Brito, Victor A. E. Farias et al. · 0 citations
Preprint Aug 2026

VTRQ: Enabling Verifiable Trajectory Range Queries in Hybrid-Storage Blockchains

Due to their increasingly large volumes, outsourcing of trajectory storage and querying to third-party service providers has become attractive. However, in such outsourced environments, service providers may return incorrect, e.g., incomplete, tampered, or invalid query results, making verifiability of query results an...

Zhong-Ming Yao, Jun-Chang Xin, Yumeng Song et al. · 1 citation

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