Saehan Jo

According to our database, Saehan Jo authored at least 16 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

ThalamusDB: Approximate Query Processing on Multi-Modal Data.

Saehan Jo, Immanuel Trummer

Proc. ACM Manag. Data, 2024

SMART: Automatically Scaling Down Language Models with Accuracy Guarantees for Reduced Processing Fees.

Saehan Jo, Immanuel Trummer

CoRR, 2024

2023

Demonstration of ThalamusDB: Answering Complex SQL Queries with Natural Language Predicates on Multi-Modal Data.

Saehan Jo, Immanuel Trummer

Proceedings of the Companion of the 2023 International Conference on Management of Data, 2023

2022

ISUM: Efficiently Compressing Large and Complex Workloads for Scalable Index Tuning.

Tarique Siddiqui, Saehan Jo, Wentao Wu, Chi Wang, Vivek R. Narasayya, Surajit Chaudhuri

Proceedings of the SIGMOD '22: International Conference on Management of Data, Philadelphia, PA, USA, June 12, 2022

2021

SkinnerDB: Regret-bounded Query Evaluation via Reinforcement Learning.

Immanuel Trummer, Junxiong Wang, Ziyun Wei, Deepak Maram, Samuel Moseley, Saehan Jo, Joseph Antonakakis, Ankush Rayabhari

ACM Trans. Database Syst., 2021

2020

Demonstration of ScroogeDB: Getting More Bang For the Buck with Deterministic Approximation in the Cloud.

Saehan Jo, Jialing Pei, Immanuel Trummer

Proc. VLDB Endow., 2020

Demonstration of BitGourmet: Data Analysis via Deterministic Approximation.

Saehan Jo, Immanuel Trummer

Proceedings of the 2020 International Conference on Management of Data, 2020

BitGourmet: Deterministic Approximation via Optimized Bit Selection.

Saehan Jo, Immanuel Trummer

Proceedings of the 10th Conference on Innovative Data Systems Research, 2020

2019

Mining an "Anti-Knowledge Base" from Wikipedia Updates with Applications to Fact Checking and Beyond.

Georgios Karagiannis, Immanuel Trummer, Saehan Jo, Shubham Khandelwal, Xuezhi Wang, Cong Yu

Proc. VLDB Endow., 2019

AggChecker: A Fact-Checking System for Text Summaries of Relational Data Sets.

Saehan Jo, Immanuel Trummer, Weicheng Yu, Xuezhi Wang, Cong Yu, Daniel Liu, Niyati Mehta

Proc. VLDB Endow., 2019

SkinnerDB: Regret-Bounded Query Evaluation via Reinforcement Learning.

Immanuel Trummer, Junxiong Wang, Deepak Maram, Samuel Moseley, Saehan Jo, Joseph Antonakakis

Proceedings of the 2019 International Conference on Management of Data, 2019

Verifying Text Summaries of Relational Data Sets.

Saehan Jo, Immanuel Trummer, Weicheng Yu, Xuezhi Wang, Cong Yu, Daniel Liu, Niyati Mehta

Proceedings of the 2019 International Conference on Management of Data, 2019

2018

SkinnerDB: Regret-Bounded Query Evaluation via Reinforcement Learning.

Immanuel Trummer, Samuel Moseley, Deepak Maram, Saehan Jo, Joseph Antonakakis

Proc. VLDB Endow., 2018

The FactChecker: Verifying Text Summaries of Relational Data Sets.

Saehan Jo, Immanuel Trummer, Weicheng Yu, Daniel Liu, Niyati Mehta

CoRR, 2018

Fast and Scalable Distributed Loopy Belief Propagation on Real-World Graphs.

Saehan Jo, Jaemin Yoo, U Kang

Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining, 2018

2017

Supervised Belief Propagation: Scalable Supervised Inference on Attributed Networks.

Jaemin Yoo, Saehan Jo, U Kang

Proceedings of the 2017 IEEE International Conference on Data Mining, 2017