Preprint
Weakest Bidder Types and New Core-Selecting Combinatorial Auctions
How Much Data Is Sufficient to Learn High-Performing Algorithms?
Learning to Branch: Generalization Guarantees and Limits of Data-Independent Discretization
LEARNING TO RELAX: SETTING SOLVER PARAMETERS ACROSS A SEQUENCE OF LINEAR SYSTEM INSTANCES
New Guarantees for Learning Revenue Maximizing Menus of Lotteries and Two-Part Tariffs
New Sequence-Independent Lifting Techniques for Cover Inequalities and When They Induce Facets
SPECTRALLY TRANSFORMED KERNEL REGRESSION
LABEL PROPAGATION WITH WEAK SUPERVISION