9 citations · 14 across the 10 of their papers we have counts for
13 papers
Algorithmic Collusion at Test Time: A Meta-game Design and Evaluation
Yuhong Luo, Daniel Schoepflin, Xintong Wang
The threat of algorithmic collusion, and whether it merits regulatory intervention, remains debated, as existing evaluations of its emergence often rely on long learning horizons,…
Strategyproof Tournament Rules for Teams with a Constant Degree of Selfishness
David Pennock, Daniel Schoepflin, Kangning Wang
We revisit the well-studied problem of designing fair and manipulation-resistant tournament rules. In this problem, we seek a mechanism that (probabilistically) identifies the winn…
On the Power of Randomization for Obviously Strategy-Proof Mechanisms
Shiri Ron, Daniel Schoepflin
We investigate the problem of designing randomized obviously strategy-proof (OSP) mechanisms in several canonical auction settings. Obvious strategy-proofness, introduced by Li [Am…
Clock Auctions Augmented with Unreliable Advice
Vasilis Gkatzelis, Daniel Schoepflin, Xizhi Tan
We provide the first analysis of (deferred acceptance) clock auctions in the learning-augmented framework. These auctions satisfy a unique list of appealing properties, including o…
Multi-Parameter Mechanisms for Consumer Surplus Maximization
Tomer Ezra, Daniel Schoepflin, Ariel Shaulker
We consider the problem of designing auctions which maximize consumer surplus (i.e., the social welfare minus the payments charged to the buyers). In the consumer surplus maximizat…
Industrial Segment Anything -- a Case Study in Aircraft Manufacturing, Intralogistics, Maintenance, Repair, and Overhaul
Keno Moenck, Arne Wendt, Philipp Prünte +9
Deploying deep learning-based applications in specialized domains like the aircraft production industry typically suffers from the training data availability problem. Only a few da…