18 citations · 55 across the 7 of their papers we have counts for
10 papers
Coercive at the equilibrium, monotone nowhere: exact convergence certificates for learning in first-price auctions
Benjamin Lubin
The Bayes-Nash equilibria of an auction are the solutions of a variational inequality, and for standard auctions its operator fails every monotonicity notion, so the theory of mono…
iMLCA: Machine Learning-powered Iterative Combinatorial Auctions with Interval Bidding
Benjamin Lubin, Manuel Beyeler, Gianluca Brero +1
Preference elicitation is a major challenge in large combinatorial auctions because the bundle space grows exponentially in the number of items. Recent work has used machine learni…
Fourier Analysis-based Iterative Combinatorial Auctions
Jakob Weissteiner, Chris Wendler, Sven Seuken +2
Recent advances in Fourier analysis have brought new tools to efficiently represent and learn set functions. In this paper, we bring the power of Fourier analysis to the design of…
Machine Learning-powered Iterative Combinatorial Auctions
Gianluca Brero, Benjamin Lubin, Sven Seuken
We present a machine learning-powered iterative combinatorial auction (MLCA). The main goal of integrating machine learning (ML) into the auction is to improve preference elicitati…
Computing Bayes-Nash Equilibria in Combinatorial Auctions with Verification
Vitor Bosshard, Benedikt Bünz, Benjamin Lubin +1
We present a new algorithm for computing pure-strategy -Bayes-Nash equilibria (-BNEs) in combinatorial auctions with continuous value and action spaces. A…
Games and Meta-Games: Pricing Rules for Combinatorial Mechanisms
Benjamin Lubin
In settings where full incentive-compatibility is not available, such as core-constraint combinatorial auctions and budget-balanced combinatorial exchanges, we may wish to design m…
Spectral goodness of fit for network models
Jesse Shore, Benjamin Lubin
We introduce a new statistic, 'spectral goodness of fit' (SGOF) to measure how well a network model explains the structure of an observed network. SGOF provides an absolute measure…
Communication Network Design: Balancing Modularity and Mixing via Optimal Graph Spectra
Benjamin Lubin, Jesse Shore, Vatche Ishakian
By leveraging information technologies, organizations now have the ability to design their communication networks and crowdsourcing platforms to pursue various performance goals, b…
Payment Rules through Discriminant-Based Classifiers
Paul Duetting, Felix Fischer, Pitchayut Jirapinyo +3
In mechanism design it is typical to impose incentive compatibility and then derive an optimal mechanism subject to this constraint. By replacing the incentive compatibility requir…
Quantifying the Strategyproofness of Mechanisms via Metrics on Payoff Distributions
Benjamin Lubin, David C. Parkes
Strategyproof mechanisms provide robust equilibrium with minimal assumptions about knowledge and rationality but can be unachievable in combination with other desirable properties…