17 citations · 47 across the 5 of their papers we have counts for
5 papers
Production Machine Learning Pipelines: Empirical Analysis and Optimization Opportunities
Doris Xin, Hui Miao, Aditya Parameswaran +1
Machine learning (ML) is now commonplace, powering data-driven applications in various organizations. Unlike the traditional perception of ML in research, ML production pipelines a…
Understanding Data Science Lifecycle Provenance via Graph Segmentation and Summarization
Hui Miao, Amol Deshpande
Increasingly modern data science platforms today have non-intrusive and extensible provenance ingestion mechanisms to collect rich provenance and context information, handle modifi…
ModelHub: Towards Unified Data and Lifecycle Management for Deep Learning
Hui Miao, Ang Li, Larry S. Davis +1
Deep learning has improved state-of-the-art results in many important fields, and has been the subject of much research in recent years, leading to the development of several syste…
ProvDB: A System for Lifecycle Management of Collaborative Analysis Workflows
Hui Miao, Amit Chavan, Amol Deshpande
As data-driven methods are becoming pervasive in a wide variety of disciplines, there is an urgent need to develop scalable and sustainable tools to simplify the process of data sc…
A Hypergraph-Partitioned Vertex Programming Approach for Large-scale Consensus Optimization
Hui Miao, Xiangyang Liu, Bert Huang +1
In modern data science problems, techniques for extracting value from big data require performing large-scale optimization over heterogenous, irregularly structured data. Much of t…