176 citations · 401 across the 23 of their papers we have counts for
6 papers · 1 filter
Towards Practical Learned Indexing
Mihail Stoian, Andreas Kipf, Ryan Marcus +1
Latest research proposes to replace existing index structures with learned models. However, current learned indexes tend to have many hyperparameters, often do not provide any erro…
Defeating duplicates: A re-design of the LearnedSort algorithm
Ani Kristo, Kapil Vaidya, Tim Kraska
LearnedSort is a novel sorting algorithm that, unlike traditional methods, uses fast ML models to boost the sorting speed. The models learn to estimate the input's distribution and…
When Are Learned Models Better Than Hash Functions?
Ibrahim Sabek, Kapil Vaidya, Dominik Horn +2
In this work, we aim to study when learned models are better hash functions, particular for hash-maps. We use lightweight piece-wise linear models to replace the hash functions as…
LEA: A Learned Encoding Advisor for Column Stores
Lujing Cen, Andreas Kipf, Ryan Marcus +1
Data warehouses organize data in a columnar format to enable faster scans and better compression. Modern systems offer a variety of column encodings that can reduce storage footpri…
TagMe: GPS-Assisted Automatic Object Annotation in Videos
Songtao He, Favyen Bastani, Mohammad Alizadeh +4
Training high-accuracy object detection models requires large and diverse annotated datasets. However, creating these data-sets is time-consuming and expensive since it relies on h…
Flow-Loss: Learning Cardinality Estimates That Matter
Parimarjan Negi, Ryan Marcus, Andreas Kipf +4
Previous approaches to learned cardinality estimation have focused on improving average estimation error, but not all estimates matter equally. Since learned models inevitably make…