Ellen Vitercik
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| title | conference | date |
|---|---|---|
| ML for discrete optimization: Theoretical foundations | Graph Learning Meets Theoretical Computer Science 2025 | 2025-08-11 |
Presents two concrete methods with proofs and experiments: a GNN pipeline called MAGNOLIA trains on exponential-time marginal value-to-go labels from tiny… | ||
| Machine Learning For Algorithm Design | Data-Driven Decision Processes Boot Camp 2022 | 2022-08-22 |
Survey of concrete claims and tools: performance of parameterized combinatorial algorithms is piecewise constant in parameters on each input, so learning… | ||
| Mechanism Design Via Machine Learning: Overfitting, Incentives, and Privacy | Meet the Fellows Welcome Event | 2021-09-08 |
Research shows how to tune a parameterized auction family—most simply the second-price (Vickrey) auction with reserve rho—by optimizing empirical revenue on a… | ||
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