Search Results for author: Neoklis Polyzotis

Found 6 papers, 2 papers with code

What can Data-Centric AI Learn from Data and ML Engineering?

no code implementations13 Dec 2021 Neoklis Polyzotis, Matei Zaharia

Data-centric AI is a new and exciting research topic in the AI community, but many organizations already build and maintain various "data-centric" applications whose goal is to produce high quality data.

Improving Differentially Private Models with Active Learning

no code implementations2 Oct 2019 Zhengli Zhao, Nicolas Papernot, Sameer Singh, Neoklis Polyzotis, Augustus Odena

Broad adoption of machine learning techniques has increased privacy concerns for models trained on sensitive data such as medical records.

Active Learning

Automated Data Slicing for Model Validation:A Big data - AI Integration Approach

no code implementations16 Jul 2018 Yeounoh Chung, Tim Kraska, Neoklis Polyzotis, Ki Hyun Tae, Steven Euijong Whang

As machine learning systems become democratized, it becomes increasingly important to help users easily debug their models.

Clustering Fairness +1

The Case for Learned Index Structures

8 code implementations4 Dec 2017 Tim Kraska, Alex Beutel, Ed H. Chi, Jeffrey Dean, Neoklis Polyzotis

Indexes are models: a B-Tree-Index can be seen as a model to map a key to the position of a record within a sorted array, a Hash-Index as a model to map a key to a position of a record within an unsorted array, and a BitMap-Index as a model to indicate if a data record exists or not.

Management Position

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