Neoklis Polyzotis

TL;DR: In this paper, the authors propose to replace traditional index structures with learned models, which can have significant advantages over traditional indexes, and theoretically analyze under which conditions learned indexes outperform traditional index structure and describe the main challenges in designing learned index structures.

TL;DR: TensorFlow Extended (TFX) is presented, a TensorFlow-based general-purpose machine learning platform implemented at Google that was able to standardize the components, simplify the platform configuration, and reduce the time to production from the order of months to weeks, while providing platform stability that minimizes disruptions.

TL;DR: This work proposes SeeDB, a visualization recommendation engine to facilitate fast visual analysis: given a subset of data to be studied, SeeDB intelligently explores the space of visualizations, evaluates promising visualizations for trends, and recommends those it deems most “useful” or “interesting”.

TL;DR: Deterministic and probabilistic algorithms to optimize the expected cost (i.e., number of questions) and expected error and can form an integral part of any query processor that uses human computation.

TL;DR: GoodS is a project to rethink how structured datasets at scale are organized at scale, in a setting where teams use diverse and often idiosyncratic ways to produce the datasets and where there is no centralized system for storing and querying them.