Kickoff

Kickoff

Tim Kraska

Industry Keynote

A 3-year History of Instance Optimized DB Research at Microsoft

Umar Farooq Minhas

Session 1: ML-enhanced Query Optimization

Logical Query Optimization

‪Xuanhe Zhou

Learned DBMS Components 2.0: From Workload-Driven to Zero-Shot Learning

Benjamin Hilprecht

Instance-Optimized Indexes and Data Layouts

Jialin Ding

Lunch

Industry Keynote

Machine Programming and the Future of Software Development

Justin Gottschlich

Session 2: ML-enhanced Query Optimization

The missing piece in ML-based query optimization

Zoi Kaoudi

Cardinality Estimation in the Learned Systems Era

Andreas Kipf

Break

Session 3: ML-enhanced Data Structures

The design of learning-based compressed data structures

Giorgio Vinciguerra

To B-tree or not to B-tree: Bridging the gap between algorithmic and learned indexes

Ali Hadian

A Self-Designing Storage Engine

Subarna Chatterjee

Break

Session 4: ML-enhanced Systems

Lessons Learned from Three Years of Learned Query Optimization

Ryan Marcus

Leveraging ML to Handle the Increasing Complexity of the Cloud

Christina Delimitrou

From WiscKey to Bourbon: A Learned Index for Log-Structured Merge Trees

Aishwarya Ganesan

Break

Session 5: ML-enhanced algorithms and other considerations

Learned Data Synopses: The Good, the Bad, the Ugly

Sanjay Krishnan

Online Learning to Join

Arash Termehchy

Practical Aspects of Systems that Learn

Alekh Jindal