activity
20122020
most citedEfficient Online Learning of Optimal Rankings: Dimensionality Reduction via Gradient Descent

3 citations · 3 across the 3 of their papers we have counts for

collaborators

5 papers

cs.LG20203 cited

Efficient Online Learning of Optimal Rankings: Dimensionality Reduction via Gradient Descent

Dimitris Fotakis, Thanasis Lianeas, Georgios Piliouras +1

We consider a natural model of online preference aggregation, where sets of preferred items along with a demand for items in each , appear online…

cs.GT2020

No-regret learning and mixed Nash equilibria: They do not mix

Lampros Flokas, Emmanouil-Vasileios Vlatakis-Gkaragkounis, Thanasis Lianeas +2

Understanding the behavior of no-regret dynamics in general -player games is a fundamental question in online learning and game theory. A folk result in the field states that, i…

cs.CC2019

Node Max-Cut and Computing Equilibria in Linear Weighted Congestion Games

Dimitris Fotakis, Vardis Kandiros, Thanasis Lianeas +3

In this work, we seek a more refined understanding of the complexity of local optimum computation for Max-Cut and pure Nash equilibrium (PNE) computation for congestion games with…

cs.GT2017

Reconciling Selfish Routing with Social Good

Soumya Basu, Ger Yang, Thanasis Lianeas +2

Selfish routing is a central problem in algorithmic game theory, with one of the principal applications being that of routing in road networks. Inspired by the emergence of routing…

cs.GT2012

On the Hardness of Network Design for Bottleneck Routing Games

Dimitris Fotakis, Alexis C. Kaporis, Thanasis Lianeas +1

In routing games, the network performance at equilibrium can be significantly improved if we remove some edges from the network. This counterintuitive fact, widely known as Braess'…