33 citations · 74 across the 12 of their papers we have counts for
12 papers
Privacy-Preserving Redaction of Diagnosis Data through Source Code Analysis
Lixi Zhou, Lei Yu, Jia Zou +1
Protecting sensitive information in diagnostic data such as logs, is a critical concern in the industrial software diagnosis and debugging process. While there are many tools devel…
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…
Benchmark of DNN Model Search at Deployment Time
Lixi Zhou, Arindam Jain, Zijie Wang +3
Deep learning has become the most popular direction in machine learning and artificial intelligence. However, the preparation of training data, as well as model training, are often…
Serving Deep Learning Models with Deduplication from Relational Databases
Lixi Zhou, Jiaqing Chen, Amitabh Das +4
There are significant benefits to serve deep learning models from relational databases. First, features extracted from databases do not need to be transferred to any decoupled deep…
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…
It's the Best Only When It Fits You Most: Finding Related Models for Serving Based on Dynamic Locality Sensitive Hashing
Lixi Zhou, Zijie Wang, Amitabh Das +1
In recent, deep learning has become the most popular direction in machine learning and artificial intelligence. However, preparation of training data is often a bottleneck in the l…
Tensor Relational Algebra for Machine Learning System Design
Binhang Yuan, Dimitrije Jankov, Jia Zou +3
We consider the question: what is the abstraction that should be implemented by the computational engine of a machine learning system? Current machine learning systems typically pu…
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…
Pangea: Monolithic Distributed Storage for Data Analytics
Jia Zou, Arun Iyengar, Chris Jermaine
Storage and memory systems for modern data analytics are heavily layered, managing shared persistent data, cached data, and non-shared execution data in separate systems such as di…
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…