activity
20162023
most citedOptimally Deceiving a Learning Leader in Stackelberg Games

11 citations · 26 across the 9 of their papers we have counts for

collaborators

12 papers

cs.GT2023★ 1 cited

Optimal Testing and Containment Strategies for Universities in Mexico amid COVID-19

Luis Benavides-Vázquez, Héctor Alonso Guzmán-Gutiérrez, Jakob Jonnerby +5

This work sets out a testing and containment framework developed for reopening universities in Mexico following the lockdown due to COVID-19. We treat diagnostic testing as a resou…

cs.GT2022

Welfare-Maximizing Pooled Testing

Simon Finster, Michelle González Amador, Edwin Lock +3

Pooled testing increases the reach of scarce diagnostic resources, but optimally composing pools for individuals differing in infection risk and the utility they derive from a nega…

cs.GT2022★ 5 cited

Differential Liquidity Provision in Uniswap v3 and Implications for Contract Design

Zhou Fan, Francisco Marmolejo-Cossío, Ben Altschuler +3

Decentralized exchanges (DEXs) provide a means for users to trade pairs of assets on-chain without the need for a trusted third party to effectuate a trade. Amongst these, constant…

cs.CR2021

Strategic Liquidity Provision in Uniswap v3

Zhou Fan, Francisco Marmolejo-Cossío, Daniel J. Moroz +3

Uniswap v3 is the largest decentralized exchange for digital currencies. A novelty of its design is that it allows a liquidity provider (LP) to allocate liquidity to one or more cl…

cs.GT2021★ 2 cited

RPPLNS: Pay-per-last-N-shares with a Randomised Twist

Philip Lazos, Francisco J. Marmolejo-Cossío, Xinyu Zhou +1

"Pay-per-last--shares" (PPLNS) is one of the most common payout strategies used by mining pools in Proof-of-Work (PoW) cryptocurrencies. As with any payment scheme, it is impera…

cs.GT2020★ 11 cited

Optimally Deceiving a Learning Leader in Stackelberg Games

Georgios Birmpas, Jiarui Gan, Alexandros Hollender +3

Recent results in the ML community have revealed that learning algorithms used to compute the optimal strategy for the leader to commit to in a Stackelberg game, are susceptible to…

cs.GT2020

Learning Strong Substitutes Demand via Queries

Paul W. Goldberg, Edwin Lock, Francisco Marmolejo-Cossío

This paper addresses the computational challenges of learning strong substitutes demand when given access to a demand (or valuation) oracle. Strong substitutes demand generalises t…

q-bio.PE2020★ 7 cited

Maximising the Benefits of an Acutely Limited Number of COVID-19 Tests

Jakob Jonnerby, Philip Lazos, Edwin Lock +4

We propose a novel testing and containment strategy in order to contain the spread of SARS-CoV2 while permitting large parts of the population to resume social and economic activit…

cs.CR2019

Fairness and Efficiency in DAG-based Cryptocurrencies

Georgios Birmpas, Elias Koutsoupias, Philip Lazos +1

Bitcoin is a decentralised digital currency that serves as an alternative to existing transaction systems based on an external central authority for security. Although Bitcoin has…

cs.GT2019

Competing (Semi)-Selfish Miners in Bitcoin

Francisco J. Marmolejo-Cossío, Eric Brigham, Benjamin Sela +1

The Bitcoin protocol prescribes certain behavior by the miners who are responsible for maintaining and extending the underlying blockchain; in particular, miners who successfully s…

cs.GT2018

Learning Convex Partitions and Computing Game-theoretic Equilibria from Best Response Queries

Paul W. Goldberg, Francisco J. Marmolejo-Cossío

Suppose that an -simplex is partitioned into convex regions having disjoint interiors and distinct labels, and we may learn the label of any point by querying it. The learni…

cs.GT2016

Logarithmic Query Complexity for Approximate Nash Computation in Large Games

Paul W. Goldberg, Francisco J. Marmolejo-Cossío, Zhiwei Steven Wu

We investigate the problem of equilibrium computation for "large" -player games. Large games have a Lipschitz-type property that no single player's utility is greatly affected b…