33 citations · 40 across the 3 of their papers we have counts for
6 papers · 1 filter
DeepMapping: Learned Data Mapping for Lossless Compression and Efficient Lookup
Lixi Zhou, K. Selçuk Candan, Jia Zou
Storing tabular data to balance storage and query efficiency is a long-standing research question in the database community. In this work, we argue and show that a novel DeepMappin…
A Comparison of Decision Forest Inference Platforms from A Database Perspective
Hong Guan, Mahidhar Reddy Dwarampudi, Venkatesh Gunda +3
Decision forest, including RandomForest, XGBoost, and LightGBM, is one of the most popular machine learning techniques used in many industrial scenarios, such as credit card fraud…
Survive the Schema Changes: Integration of Unmanaged Data Using Deep Learning
Zijie Wang, Lixi Zhou, Amitabh Das +3
Data is the king in the age of AI. However data integration is often a laborious task that is hard to automate. Schema change is one significant obstacle to the automation of the e…
Lachesis: Automatic Partitioning for UDF-Centric Analytics
Jia Zou, Amitabh Das, Pratik Barhate +4
Persistent partitioning is effective in avoiding expensive shuffling operations. However it remains a significant challenge to automate this process for Big Data analytics workload…
Declarative Recursive Computation on an RDBMS, or, Why You Should Use a Database For Distributed Machine Learning
Dimitrije Jankov, Shangyu Luo, Binhang Yuan +4
A number of popular systems, most notably Google's TensorFlow, have been implemented from the ground up to support machine learning tasks. We consider how to make a very small set…
PlinyCompute: A Platform for High-Performance, Distributed, Data-Intensive Tool Development
Jia Zou, R. Matthew Barnett, Tania Lorido-Botran +6
This paper describes PlinyCompute, a system for development of high-performance, data-intensive, distributed computing tools and libraries. In the large, PlinyCompute presents the…