11 citations · 11 across the 2 of their papers we have counts for
6 papers
LISA: Towards Learned DNA Sequence Search
Darryl Ho, Jialin Ding, Sanchit Misra +4
Next-generation sequencing (NGS) technologies have enabled affordable sequencing of billions of short DNA fragments at high throughput, paving the way for population-scale genomics…
Neo: A Learned Query Optimizer
Ryan Marcus, Parimarjan Negi, Hongzi Mao +5
Query optimization is one of the most challenging problems in database systems. Despite the progress made over the past decades, query optimizers remain extremely complex component…
Precision and Recall for Time Series
Nesime Tatbul, Tae Jun Lee, Stan Zdonik +2
Classical anomaly detection is principally concerned with point-based anomalies, those anomalies that occur at a single point in time. Yet, many real-world anomalies are range-base…
Precision and Recall for Range-Based Anomaly Detection
Tae Jun Lee, Justin Gottschlich, Nesime Tatbul +2
Classical anomaly detection is principally concerned with point-based anomalies, anomalies that occur at a single data point. In this paper, we present a new mathematical model to…
Greenhouse: A Zero-Positive Machine Learning System for Time-Series Anomaly Detection
Tae Jun Lee, Justin Gottschlich, Nesime Tatbul +2
This short paper describes our ongoing research on Greenhouse - a zero-positive machine learning system for time-series anomaly detection.
S-Store: Streaming Meets Transaction Processing
John Meehan, Nesime Tatbul, Stan Zdonik +10
Stream processing addresses the needs of real-time applications. Transaction processing addresses the coordination and safety of short atomic computations. Heretofore, these two mo…