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Kwanghyun Park

3 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author3

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.DB3

identity via Semantic Scholar / OpenAlex

most citedExtending Relational Query Processing with ML Inference

16 citations · 21 across the 2 of their papers we have counts for

collaborators

3 papers

cs.DB2020★ 5 cited

Lessons learned from the early performance evaluation of Intel Optane DC Persistent Memory in DBMS

Yinjun Wu, Kwanghyun Park, Rathijit Sen +2

Non-volatile memory (NVM) is an emerging technology, which has the persistence characteristics of large capacity storage devices(e.g., HDDs and SSDs), while providing the low acces…

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

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…

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