How can a data system make uncertainty, tradeoffs, and future behavior visible?
This program connects systems that diagnose and predict performance with systems that make explicit tradeoffs around latency, accuracy, and robustness. It provides the intellectual lineage for current work on systems that learn and optimize their own behavior.
Methods and questions
- performance modeling
- diagnosis
- robust optimization
- approximate query processing
- workload intelligence