Jialin Ding

According to our database, Jialin Ding authored at least 18 papers between 2014 and 2023.

Collaborative distances:

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

2023

Enhancing In-Memory Spatial Indexing with Learned Search.

Varun Pandey, Alexander van Renen, Eleni Tzirita Zacharatou, Andreas Kipf, Ibrahim Sabek, Jialin Ding, Volker Markl, Alfons Kemper

CoRR, 2023

Distribution Free Domain Generalization.

Peifeng Tong, Wu Su, He Li, Jialin Ding, Zhan Haoxiang, Song Xi Chen

Proceedings of the International Conference on Machine Learning, 2023

2022

SageDB: An Instance-Optimized Data Analytics System.

Jialin Ding, Ryan Marcus, Andreas Kipf, Vikram Nathan, Aniruddha Nrusimha, Kapil Vaidya, Alexander van Renen, Tim Kraska

Proc. VLDB Endow., 2022

Self-Organizing Data Containers.

Samuel Madden, Jialin Ding, Tim Kraska, Sivaprasad Sudhir, David E. Cohen, Timothy G. Mattson, Nesime Tatbul

Proceedings of the 12th Conference on Innovative Data Systems Research, 2022

2021

APEX: A High-Performance Learned Index on Persistent Memory.

Baotong Lu, Jialin Ding, Eric Lo, Umar Farooq Minhas, Tianzheng Wang

Proc. VLDB Endow., 2021

Instance-Optimized Data Layouts for Cloud Analytics Workloads.

Jialin Ding, Umar Farooq Minhas, Badrish Chandramouli, Chi Wang, Yinan Li, Ying Li, Donald Kossmann, Johannes Gehrke, Tim Kraska

Proceedings of the SIGMOD '21: International Conference on Management of Data, 2021

2020

Tsunami: A Learned Multi-dimensional Index for Correlated Data and Skewed Workloads.

Jialin Ding, Vikram Nathan, Mohammad Alizadeh, Tim Kraska

Proc. VLDB Endow., 2020

Cortex: Harnessing Correlations to Boost Query Performance.

Vikram Nathan, Jialin Ding, Tim Kraska, Mohammad Alizadeh

CoRR, 2020

The Case for Learned Spatial Indexes.

Varun Pandey, Alexander van Renen, Andreas Kipf, Jialin Ding, Ibrahim Sabek, Alfons Kemper

Proceedings of the AIDB@VLDB 2020, 2020

Learning Multi-Dimensional Indexes.

Vikram Nathan, Jialin Ding, Mohammad Alizadeh, Tim Kraska

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

ALEX: An Updatable Adaptive Learned Index.

Jialin Ding, Umar Farooq Minhas, Jia Yu, Chi Wang, Jaeyoung Do, Yinan Li, Hantian Zhang, Badrish Chandramouli, Johannes Gehrke, Donald Kossmann, David B. Lomet, Tim Kraska

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

2019

LISA: Towards Learned DNA Sequence Search.

Darryl Ho, Jialin Ding, Sanchit Misra, Nesime Tatbul, Vikram Nathan, Md. Vasimuddin, Tim Kraska

CoRR, 2019

ALEX: An Updatable Adaptive Learned Index.

Jialin Ding, Umar Farooq Minhas, Hantian Zhang, Yinan Li, Chi Wang, Badrish Chandramouli, Johannes Gehrke, Donald Kossmann, David B. Lomet

CoRR, 2019

2018

MacroBase: Prioritizing Attention in Fast Data.

Firas Abuzaid, Peter Bailis, Jialin Ding, Edward Gan, Samuel Madden, Deepak Narayanan, Kexin Rong, Sahaana Suri

ACM Trans. Database Syst., 2018

Moment-Based Quantile Sketches for Efficient High Cardinality Aggregation Queries.

Edward Gan, Jialin Ding, Kai Sheng Tai, Vatsal Sharan, Peter Bailis

Proc. VLDB Endow., 2018

2014

Relaxed stability conditions for interval type-2 fuzzy-model-based control systems.

Tao Zhao, Jian Xiao, Jialin Ding, XueSong Deng, Song Wang

Kybernetika, 2014

A variable precision interval type-2 fuzzy rough set model for attribute reduction.

Tao Zhao, Jian Xiao, Jialin Ding, Peng Chen

J. Intell. Fuzzy Syst., 2014

Distributed State Estimation for Discrete-Time Nonlinear System with Unknown Inputs.

Jialin Ding, Jian Xiao, Yong Zhang, Muhammad Naveed Iqbal

Circuits Syst. Signal Process., 2014