• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 48 matches

• 2024
• 
  Jan-Micha Bodensohn, Carsten Binnig:
  Rethinking Table Retrieval from Data Lakes. aiDM@SIGMOD 2024: 2:1-2:5
• 
  Jenny Gao, Jialin Ding, Sivaprasad Sudhir, Samuel Madden:
  Learning Bit Allocations for Z-Order Layouts in Analytic Data Systems. aiDM@SIGMOD 2024: 5:1-5:9
• 
  Hasan M. Jamil:
  Smart Science Needs Linked Open Data with a Dash of Large Language Models and Extended Relations. aiDM@SIGMOD 2024: 1:1-1:11
• 
  Amadou Latyr Ngom, Tim Kraska:
  Mallet: SQL Dialect Translation with LLM Rule Generation. aiDM@SIGMOD 2024: 3:1-3:5
• 
  Zixuan Yi, Yao Tian, Zachary G. Ives, Ryan Marcus:
  Low Rank Approximation for Learned Query Optimization. aiDM@SIGMOD 2024: 4:1-4:5
• 
  Proceedings of the Seventh International Workshop on Exploiting Artificial Intelligence Techniques for Data Management, aiDM 2024, Santiago, Chile, 14 June 2024. ACM 2024 [contents]
• 2023
• 
  Mohamed Abdelaal, Rashmi Koparde, Harald Schöning:
  AutoCure: Automated Tabular Data Curation Technique for ML Pipelines. aiDM@SIGMOD 2023: 1:1-1:11
• 
  Pratyush Agnihotri, Boris Koldehofe, Carsten Binnig, Manisha Luthra:
  Zero-Shot Cost Models for Parallel Stream Processing. aiDM@SIGMOD 2023: 5:1-5:5
• 
  Damjan Gjurovski, Sebastian Michel:
  Tuple Bubbles: Learned Tuple Representations for Tunable Approximate Query Processing. aiDM@SIGMOD 2023: 2:1-2:9
• 
  Zhitao Gong, Wenlu Wang:
  Adversarial and Clean Data Are Not Twins. aiDM@SIGMOD 2023: 6:1-6:5
• 
  Keizo Hori, Yuya Sasaki, Daichi Amagata, Yuki Murosaki, Makoto Onizuka:
  Learned Spatial Data Partitioning. aiDM@SIGMOD 2023: 3:1-3:8
• 
  Matthias Urban, Duc Dat Nguyen, Carsten Binnig:
  OmniscientDB: A Large Language Model-Augmented DBMS That Knows What Other DBMSs Do Not Know. aiDM@SIGMOD 2023: 4:1-4:7
• 
  Rajesh Bordawekar, Oded Shmueli, Yael Amsterdamer, Donatella Firmani, Andreas Kipf:
  Proceedings of the Sixth International Workshop on Exploiting Artificial Intelligence Techniques for Data Management, aiDM@SIGMOD 2023, Seattle, WA, USA, 18 June 2023. ACM 2023 [contents]
• 2022
• 
  Mikkel Møller Andersen, Pinar Tözün:
  Micro-architectural analysis of a learned index. aiDM@SIGMOD 2022: 5:1-5:12
• 
  Tamer Eldeeb, Zhengneng Chen, Asaf Cidon, Junfeng Yang:
  Neuroshard: towards automatic multi-objective sharding with deep reinforcement learning. aiDM@SIGMOD 2022: 1:1-1:12
• 
  Andreas Kipf, Dominik Horn, Pascal Pfeil, Ryan Marcus, Tim Kraska:
  LSI: a learned secondary index structure. aiDM@SIGMOD 2022: 4:1-4:5
• 
  Jin Wang, Yuliang Li, Wataru Hirota, Eser Kandogan:
  Machop: an end-to-end generalized entity matching framework. aiDM@SIGMOD 2022: 2:1-2:10
• 
  Michal Zwolak, Zainab Abbas, Sonia Horchidan, Paris Carbone, Vasiliki Kalavri:
  GCNSplit: bounding the state of streaming graph partitioning. aiDM@SIGMOD 2022: 3:1-3:12
• 
  Rajesh Bordawekar, Oded Shmueli, Yael Amsterdamer, Donatella Firmani, Ryan Marcus:
  aiDM '22: Proceedings of the Fifth International Workshop on Exploiting Artificial Intelligence Techniques for Data Management, Philadelphia, Pennsylvania, USA, 17 June 2022. ACM 2022, ISBN 978-1-4503-9377-5 [contents]
• 2021
• 
  Michael Günther, Maik Thiele, Julius Gonsior, Wolfgang Lehner:
  Pre-Trained Web Table Embeddings for Table Discovery. aiDM@SIGMOD 2021: 24-31
• 
  Lujing Cen, Andreas Kipf, Ryan Marcus, Tim Kraska:
  LEA: A Learned Encoding Advisor for Column Stores. aiDM@SIGMOD 2021: 32-35
• 
  Martin Eppert, Philipp Fent, Thomas Neumann:
  A Tailored Regression for Learned Indexes: Logarithmic Error Regression. aiDM@SIGMOD 2021: 9-15
• 
  Mayank Mishra, Rekha Singhal:
  RUSLI: Real-time Updatable Spline Learned Index. aiDM@SIGMOD 2021: 1-8
• 
  Aurélien Personnaz, Sihem Amer-Yahia, Laure Berti-Équille, Maximilian Fabricius, Srividya Subramanian:
  Balancing Familiarity and Curiosity in Data Exploration with Deep Reinforcement Learning. aiDM@SIGMOD 2021: 16-23
• 
  Mohan Zhang, Oliver Schulte, Yudong Luo:
  Leveraging Approximate Constraints for Localized Data Error Detection. aiDM@SIGMOD 2021: 36-44
• 
  Rajesh Bordawekar, Yael Amsterdamer, Oded Shmueli, Nesime Tatbul:
  aiDM '21: Fourth Workshop in Exploiting AI Techniques for Data Management, Virtual Event, China, 25 June, 2021. ACM 2021, ISBN 978-1-4503-8535-0 [contents]
• 2020
• 
  Ahmed S. Abdelhamid, Walid G. Aref:
  PartLy: learning data partitioning for distributed data stream processing. aiDM@SIGMOD 2020: 6:1-6:4
• 
  Zhiwei Fan, Rathijit Sen, Paraschos Koutris, Aws Albarghouthi:
  Automated tuning of query degree of parallelism via machine learning. aiDM@SIGMOD 2020: 2:1-2:4
• 
  Vahid Ghadakchi, Mian Xie, Arash Termehchy:
  Bandit join: preliminary results. aiDM@SIGMOD 2020: 1:1-1:4
• 
  Runsheng Benson Guo, Khuzaima Daudjee:
  Research challenges in deep reinforcement learning-based join query optimization. aiDM@SIGMOD 2020: 3:1-3:6

skipping 18 more matches