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Found 5 papers, 3 papers with code
LACS: Learning-Augmented Algorithms for Carbon-Aware Resource Scaling with Uncertain Demand
The task is to dynamically scale resources (e. g., the number of servers) assigned to a job of unknown length such that it is completed before a deadline, with the objective of reducing the carbon emissions of executing the workload.
Chasing Convex Functions with Long-term Constraints
We introduce and study a family of online metric problems with long-term constraints.
Online Conversion with Switching Costs: Robust and Learning-Augmented Algorithms
We introduce competitive (robust) threshold-based algorithms for both the minimization and maximization variants of this problem, and show they are optimal among deterministic online algorithms.
Time Fairness in Online Knapsack Problems
We propose a parameterized deterministic algorithm where the parameter precisely captures the Pareto-optimal trade-off between fairness (static pricing) and competitiveness (dynamic pricing).
FlowSense: Monitoring Airflow in Building Ventilation Systems Using Audio Sensing
With a motivation to monitor airflow from building ventilation systems through commodity sensing devices, we present FlowSense, a machine learning-based algorithm to predict airflow rate from sensed audio data in indoor spaces.
