Zekai J. Gao

According to our database, Zekai J. Gao authored at least 8 papers between 2014 and 2020.

Collaborative distances:

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

2020

Declarative Recursive Computation on an RDBMS: or, Why You Should Use a Database For Distributed Machine Learning.

Dimitrije Jankov, Shangyu Luo, Binhang Yuan, Zhuhua Cai, Jia Zou, Chris Jermaine, Zekai J. Gao

SIGMOD Rec., 2020

Scalable linear algebra on a relational database system.

Shangyu Luo, Zekai J. Gao, Michael N. Gubanov, Luis Leopoldo Perez, Dimitrije Jankov, Christopher M. Jermaine

Commun. ACM, 2020

2019

Declarative Parameterizations of User-Defined Functions for Large-Scale Machine Learning and Optimization.

Zekai J. Gao, Niketan Pansare, Christopher M. Jermaine

IEEE Trans. Knowl. Data Eng., 2019

Declarative Recursive Computation on an RDBMS.

Dimitrije Jankov, Shangyu Luo, Binhang Yuan, Zhuhua Cai, Jia Zou, Chris Jermaine, Zekai J. Gao

Proc. VLDB Endow., 2019

2018

Scalable Linear Algebra on a Relational Database System.

Shangyu Luo, Zekai J. Gao, Michael N. Gubanov, Luis Leopoldo Perez, Christopher M. Jermaine

SIGMOD Rec., 2018

2017

The BUDS Language for Distributed Bayesian Machine Learning.

Zekai J. Gao, Shangyu Luo, Luis Leopoldo Perez, Chris Jermaine

Proceedings of the 2017 ACM International Conference on Management of Data, 2017

2016

Distributed Algorithms for Computing Very Large Thresholded Covariance Matrices.

Zekai J. Gao, Chris Jermaine

ACM Trans. Knowl. Discov. Data, 2016

2014

A comparison of platforms for implementing and running very large scale machine learning algorithms.

Zhuhua Cai, Zekai J. Gao, Shangyu Luo, Luis Leopoldo Perez, Zografoula Vagena, Christopher M. Jermaine

Proceedings of the International Conference on Management of Data, 2014