Our paper "UDO: universal database optimization using reinforcement learning" by Wang et al. has been accepted to VLDB 2022!
Our paper "WebChecker: towards an infrastructure for efficient misinformation detection at Web scale" by Trummer will appear in the IEEE Data Engineering Bulletin!
Our paper "The case for NLP-enhanced database tuning: towards tuning tools that read the manual" by Trummer has been accepted for VLDB 2021!
Our paper "Robust voice querying with MUVE: optimally visualizing results of phonetically similar queries" by Wei et al. has been accepted for VLDB 2021!
Our paper "Demonstrating UDO: a unified approach for optimizing transaction code, physical design, and system parameters via reinforcement learning" by Wang et al. has been accepted to SIGMOD 2021!
Our paper "Demonstrating robust voice querying with MUVE: optimally visualizing results of phonetically similar queries" by Wei et al. has been accepted for SIGMOD 2021!
Our paper "Optimally summarizing data by small fact sets for concise answers to voice queries" by Trummer et al. has been accepted at ICDE 2021!
Our paper "SkinnerDB: regret-bounded query evaluation via reinforcement learning" by Trummer et al. has been accepted as Best of SIGMOD paper to TODS!
News 2020
Google funds our research on data-driven claim verification!
Our paper "Scrutinizer: a mixed-initiative approach to large-scale, data-driven claim verification" by George et al. was accepted at VLDB 2020!
Our paper "Demonstration of ScroogeDB: getting more bang for the buck with deterministic approximation in the Cloud" by Saehan et al. was accepted at VLDB 2020!
Our paper "Demonstrating the voice-based exploration of large data sets with CiceroDB-Zero" by Immanuel was accepted at VLDB 2020!
Our paper "Scrutinizer: fact checking statistical claims" by George et al. was accepted at VLDB 2020!
Our work on data-driven fact checking is covered by major European newspapers!
Our paper on SkinnerDB was selected for the Best of SIGMOD edition of TODS!
Our paper "Demonstration of BitGourmet: data analysis via deterministic approximation" by Saehan and Immanuel was accepted at SIGMOD 2020!
News 2019
A demo for voice-based data analysis is now online (see here).
Our paper "Mining an “Anti-Knowledge Base” from Wikipedia updates with applications to fact checking and beyond" by Georgios Karagiannis et al. was accepted at VLDB 2020!
Our paper "BitGourmet: deterministic approximation via optimized bit selection" by Saehan Jo et al. was accepted at CIDR 2020!
Our proposal "Regret-bounded query evaluation via reinforcement learning" has been selected for funding by NSF!
Videos of our four SIGMOD 2019 paper talks are now online:
Immanuel Trummer wins the Google Faculty Award for building an anti-knowledge base!
Our paper "AggChecker: a fact-checking system for text summaries of relational data sets" by Saehan Jo et al. was accepted at VLDB 2019!
News 2018
Our paper "Data vocalization with CiceroDB" by Immanuel Trummer was accepted at CIDR 2019!
Our paper "Verifying text summaries of relational data sets" by Saehan Jo et al. was accepted at SIGMOD 2019!
Our paper "SkinnerDB: regret-bounded query evaluation via reinforcement learning" by Immanuel Trummer et al. was accepted at SIGMOD 2019!
Our paper "A holistic approach for query evaluation and result vocalization in voice-based OLAP" by Immanuel Trummer et al. was accepted at SIGMOD 2019!
Our paper "Exact cardinality query optimization with bounded execution cost" by Immanuel Trummer was accepted at SIGMOD 2019!
Congrats to Samuel Moseley for winning a VLDB 2018 NSF Travel Grant!
Congrats to Mark Bryan for winning a honorable mention for the 2018 CRA Outstanding Undergraduate Researcher Award!
Our paper "Vocalizing Large Time Series Efficiently" was accepted at VLDB 2018.
Our paper "SkinnerDB: Regret-Bounded Query Evaluation via Reinforcement Learning" was accepted at VLDB 2018.
A pre-print of our paper on computational fact checking is online.
Congrats to Mark Bryan for winning the JP Morgan BOOM Award 2018 for CiceroDB!