activity
20112026
most citedWho to Trust for Truthfully Maximizing Welfare?

6 citations · 32 across the 37 of their papers we have counts for

collaborators

46 papers

cs.DC2026

FAIR-Compute: A Roadmap for Fair and Efficient Allocation of Federated Digital Research Infrastructure

Konstantinos E. Zachariadis, Ahmed Sayed, Dimitris Fotakis +2

As demand for high-performance computing (HPC), high-throughput computing and data storage grows, the way scarce compute is allocated -- not just how much exists -- has become a de…

cs.LG2023

Optimizing Solution-Samplers for Combinatorial Problems: The Landscape of Policy-Gradient Methods

Constantine Caramanis, Dimitris Fotakis, Alkis Kalavasis +2

Deep Neural Networks and Reinforcement Learning methods have empirically shown great promise in tackling challenging combinatorial problems. In those methods a deep neural network…

cs.LG2023★ 3 cited

Fairness Aware Counterfactuals for Subgroups

Loukas Kavouras, Konstantinos Tsopelas, Giorgos Giannopoulos +6

In this work, we present Fairness Aware Counterfactuals for Subgroups (FACTS), a framework for auditing subgroup fairness through counterfactual explanations. We start with revisit…

cs.LG2022

Perfect Sampling from Pairwise Comparisons

Dimitris Fotakis, Alkis Kalavasis, Christos Tzamos

In this work, we study how to efficiently obtain perfect samples from a discrete distribution given access only to pairwise comparisons of elements of its support. Sp…

cs.DS2022

Graph Connectivity with Noisy Queries

Dimitris Fotakis, Evangelia Gergatsouli, Charilaos Pipis +2

Graph connectivity is a fundamental combinatorial optimization problem that arises in many practical applications, where usually a spanning subgraph of a network is used for its op…

cs.GT2022

Sampling and Optimal Preference Elicitation in Simple Mechanisms

Ioannis Anagnostides, Dimitris Fotakis, Panagiotis Patsilinakos

In this work we are concerned with the design of efficient mechanisms while eliciting limited information from the agents. First, we study the performance of sampling approximation…