activity
20162026
most citedThe Design of Arbitrage-Free Data Pricing Schemes

11 citations · 37 across the 16 of their papers we have counts for

collaborators

20 papers

cs.AI2026

Tracing Agentic Failure from the Flow of Success

Samuel Yeh, Yiwen Zhu, Shaleen Deep +1

Failure attribution for LLM-based agentic systems, i.e., identifying which steps in a failure trajectory caused the task to fail, is critical for debugging and improving these syst…

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.DB2025

Regular Expression Indexing for Log Analysis. Extended Version

Ling Zhang, Shaleen Deep, Jignesh M. Patel +1

In this paper, we present the design and architecture of REI, a novel system for indexing log data for regular expression queries. Our main contribution is an -gram-based indexi…

cs.DB2025

An Evaluation of N-Gram Selection Strategies for Regular Expression Indexing in Contemporary Text Analysis Tasks. Extended Version

Ling Zhang, Shaleen Deep, Jignesh M. Patel +1

Efficient evaluation of regular expressions (regex, for short) is crucial for text analysis, and n-gram indexes are fundamental to achieving fast regex evaluation performance. Howe…

cs.DB2024

Output-sensitive Conjunctive Query Evaluation

Shaleen Deep, Hangdong Zhao, Austen Z. Fan +1

Join evaluation is one of the most fundamental operations performed by database systems and arguably the most well-studied problem in the Database community. A staggering number of…

cs.DB2024★ 1 cited

Evaluating Datalog over Semirings: A Grounding-based Approach

Hangdong Zhao, Shaleen Deep, Paraschos Koutris +2

Datalog is a powerful yet elegant language that allows expressing recursive computation. Although Datalog evaluation has been extensively studied in the literature, so far, only lo…