14 citations · 53 across the 15 of their papers we have counts for
5 papers · 1 filter
Saibot: A Differentially Private Data Search Platform
Zezhou Huang, Jiaxiang Liu, Daniel Alabi +2
Recent data search platforms use ML task-based utility measures rather than metadata-based keywords, to search large dataset corpora. Requesters submit a training dataset and these…
Addressing Budget Allocation and Revenue Allocation in Data Market Environments Using an Adaptive Sampling Algorithm
Boxin Zhao, Boxiang Lyu, Raul Castro Fernandez +1
High-quality machine learning models are dependent on access to high-quality training data. When the data are not already available, it is tedious and costly to obtain them. Data m…
Kitana: Efficient Data Augmentation Search for AutoML
Zezhou Huang, Pranav Subramaniam, Raul Castro Fernandez +1
AutoML services provide a way for non-expert users to benefit from high-quality ML models without worrying about model design and deployment, in exchange for a charge per hour ($21…
Data Station: Delegated, Trustworthy, and Auditable Computation to Enable Data-Sharing Consortia with a Data Escrow
Siyuan Xia, Zhiru Zhu, Chris Zhu +7
Pooling and sharing data increases and distributes its value. But since data cannot be revoked once shared, scenarios that require controlled release of data for regulatory, privac…
METAM: Goal-Oriented Data Discovery
Sainyam Galhotra, Yue Gong, Raul Castro Fernandez
Data is a central component of machine learning and causal inference tasks. The availability of large amounts of data from sources such as open data repositories, data lakes and da…