Research map / Bandits and online learning / Online convex optimization and games
Parsimonious Predictions for Strategyproof Scheduling
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Studies strategyproof makespan scheduling on unrelated strategic machines using parsimonious predictions (abstract truncated; details beyond the abstract are unknown).
Problem
Scheduling m jobs on n unrelated strategic machines to minimize maximum load when machines may misreport processing times to minimize their own load; deterministic strategyproof mechanisms are known to be n-approximate at best.
Approach
Uses parsimonious predictions (a small amount of advice) to circumvent the known best-possible n-approximation lower bound for deterministic strategyproof mechanisms; exact mechanism design details are not stated in the truncated abstract.
Limitations
- Abstract is truncated; full results not available
Experimental setup
Builds on: Nisan and Ronen mechanism
Closest papers by meaning
- Minimalistic Predictions to Schedule Jobs with Online Precedence Constraints (ICML 2023 · similarity 0.88)
- Non-clairvoyant Scheduling with Partial Predictions (ICML 2024 · similarity 0.87)
- Efficient Truthful Scheduling and Resource Allocation through Monitoring (AAAI 2021 · similarity 0.86)
- On Preemption and Learning in Stochastic Scheduling (ICML 2023 · similarity 0.86)
- What to Predict for Efficient Scheduling on Parallel Machines (NeurIPS 2026 · similarity 0.86)
- On Smoothness Bounds for Non-Clairvoyant Scheduling with Predictions (ICLR 2026 · similarity 0.85)
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