26 citations · 56 across the 9 of their papers we have counts for
14 papers · 1 filter
LSI: A Learned Secondary Index Structure
Andreas Kipf, Dominik Horn, Pascal Pfeil +2
Learned index structures have been shown to achieve favorable lookup performance and space consumption compared to their traditional counterparts such as B-trees. However, most lea…
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…
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…
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…
The Case for Distance-Bounded Spatial Approximations
Eleni Tzirita Zacharatou, Andreas Kipf, Ibrahim Sabek +3
Spatial approximations have been traditionally used in spatial databases to accelerate the processing of complex geometric operations. However, approximations are typically only us…