activity
20092026
most citedData Acquisition for Improving Machine Learning Models

38 citations · 97 across the 16 of their papers we have counts for

collaborators

18 papers

cs.DB2026

HNSW with Accuracy Guarantees Using Graph Spanners

Minghao Li, Raghav Mittal, Sanjivni Rana +3

Hierarchical Navigable Small World (HNSW) graphs serve as the industry standard due to their logarithmic complexity and strong empirical performance. However, HNSW relies on greedy…

cs.DB2023★ 2 cited

A Distributed Solution for Efficient K Shortest Paths Computation over Dynamic Road Networks

Ziqiang Yu, Xiaohui Yu, Nick Koudas +2

The problem of identifying the k-shortest paths KSPs for short in a dynamic road network is essential to many location-based services. Road networks are dynamic in the sense that t…

cs.DB2022★ 1 cited

Effective Explanations for Entity Resolution Models

Tommaso Teofili, Donatella Firmani, Nick Koudas +3

Entity resolution (ER) aims at matching records that refer to the same real-world entity. Although widely studied for the last 50 years, ER still represents a challenging data mana…

cs.DB2021★ 5 cited

LES3: Learning-based Exact Set Similarity Search

Yifan Li, Xiaohui Yu, Nick Koudas

Set similarity search is a problem of central interest to a wide variety of applications such as data cleaning and web search. Past approaches on set similarity search utilize eith…

cs.DB2021★ 38 cited

Data Acquisition for Improving Machine Learning Models

Yifan Li, Xiaohui Yu, Nick Koudas

The vast advances in Machine Learning over the last ten years have been powered by the availability of suitably prepared data for training purposes. The future of ML-enabled enterp…

cs.LG2020

Efficient Construction of Nonlinear Models over Normalized Data

Zhaoyue Chen, Nick Koudas, Zhe Zhang +1

Machine Learning (ML) applications are proliferating in the enterprise. Relational data which are prevalent in enterprise applications are typically normalized; as a result, data h…