DB-BERT: the database tuning tool that “reads” the manual.
SkinnerDB: adaptive query processing with reinforcement learning.
Publications
2022
SIGMOD 2022 Demonstrating DB-BERT: a database tuning tool that “reads the manual”. Immanuel Trummer.
AAAI 2022 Procrastinated tree search: black-box optimization with delayed, noisy, and multi-fidelity feedback. Junxiong Wang, Debabrota Basu, Immanuel Trummer.
SIGMOD 2022 DB-BERT: a database tuning tool that “reads the manual”. Immanuel Trummer.
CIDR 2022 Towards NLP-enhanced data profiling tools. (Abstract) Immanuel Trummer.
2021
TODS 2021 “Best of SIGMOD” Edition SkinnerDB: regret-bounded query evaluation via reinforcement learning. Immanuel Trummer, Junxiong Wang, Ziyun Wei et al.
VLDB 2021 UDO: universal database optimization using reinforcement learning. Junxiong Wang, Immanuel Trummer, Debabrota Basu.
VLDB 2021 The case for NLP-enhanced database tuning: towards tuning tools that read the manual. Immanuel Trummer.
VLDB 2021 Robust voice querying with MUVE: optimally visualizing results of phonetically similar queries. Ziyun Wei, Immanuel Trummer, Connor Anderson.
IEEE Data Engineering Bulletin WebChecker: towards an infrastructure for efficient misinformation detection at Web scale. Immanuel Trummer.
SIGMOD Record 2021 Database tuning using natural language processing. Immanuel Trummer.
SIGMOD 2021 Demonstrating UDO: a unified approach for optimizing transaction code, physical design, and system parameters via reinforcement learning. Junxiong Wang, Immanuel Trummer, Debabrota Basu.
SIGMOD 2021 Demonstrating robust voice querying with MUVE: optimally visualizing results of phonetically similar queries. Ziyun Wei, Immanuel Trummer, Connor Anderson.
ICDE 2021 Optimally summarizing data by small fact sets for concise answers to voice queries. Immanuel Trummer, Connor Anderson.
2020
VLDB 2020 Scrutinizer: A Mixed-Initiative Approach to Large-Scale, Data-Driven Claim Verification. George Karagiannis, Mohammed Saeed, Paolo Papotti, Immanuel Trummer.
VLDB 2020 Demonstration of ScroogeDB: getting more bang for the buck with deterministic approximation in the Cloud. Saehan Jo, Jialing Pei, Immanuel Trummer.
VLDB 2020 Demonstrating the voice-based exploration of large data sets with CiceroDB-Zero. Immanuel Trummer.
VLDB 2020 Scrutinizer: fact checking statistical claims. George Karagiannis, Mohammed Saeed, Paolo Papotti, Immanuel Trummer.
SIGMOD 2020 Demonstration of BitGourmet: data analysis via deterministic approximation. Saehan Jo, Immanuel Trummer.
VLDB 2020 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.
CIDR 2020 BitGourmet: deterministic approximation via optimized bit selections. Saehan Jo, Immanuel Trummer.
2019
VLDB 2019 AggChecker: a fact-checking system for text summaries of relational data sets. Saehan Jo, Immanuel Trummer, Weicheng Yu, Xuezhi Wang, Cong Yu, Daniel Liy Niyati Mehta.
SIGMOD 2019 SkinnerDB: Regret-bounded query evaluation via reinforcement learning. Immanuel Trummer, Junxiong Wang, Deepak Maram, Samuel Moseley, Saehan Jo, Joseph Antonakakis.
SIGMOD 2019 A holistic approach for query evaluation and result vocalization in voice-based OLAP. Immanuel Trummer, Yicheng Wang, Saketh Mahankali.
SIGMOD 2019 Exact cardinality query optimization with bounded execution cost. Immanuel Trummer.
SIGMOD 2019 Verifying text summaries of relational data sets. Saehan Jo, Immanuel Trummer, Weicheng Yu, Xuezhi Wang, Cong Yu, Daniel Liu, Niyati Mehta.
CIDR 2019 Data Vocalization with CiceroDB. Immanuel Trummer.