Search Results for author: Stefano Leonardi

Found 14 papers, 0 papers with code

The Role of Transparency in Repeated First-Price Auctions with Unknown Valuations

no code implementations14 Jul 2023 Nicolò Cesa-Bianchi, Tommaso Cesari, Roberto Colomboni, Federico Fusco, Stefano Leonardi

We study the problem of regret minimization for a single bidder in a sequence of first-price auctions where the bidder discovers the item's value only if the auction is won.

Repeated Bilateral Trade Against a Smoothed Adversary

no code implementations21 Feb 2023 Nicolò Cesa-Bianchi, Tommaso Cesari, Roberto Colomboni, Federico Fusco, Stefano Leonardi

We provide a complete characterization of the regret regimes for fixed-price mechanisms under different feedback models in the two cases where the learner can post either the same or different prices to buyers and sellers.

Fully Dynamic Online Selection through Online Contention Resolution Schemes

no code implementations8 Jan 2023 Vashist Avadhanula, Andrea Celli, Riccardo Colini-Baldeschi, Stefano Leonardi, Matteo Russo

A successful approach to online selection problems in the adversarial setting is given by the notion of Online Contention Resolution Scheme (OCRS), that uses a priori information to formulate a linear relaxation of the underlying optimization problem, whose optimal fractional solution is rounded online for any adversarial order of the input sequence.

Allocating Indivisible Goods to Strategic Agents: Pure Nash Equilibria and Fairness

no code implementations17 Sep 2021 Georgios Amanatidis, Georgios Birmpas, Federico Fusco, Philip Lazos, Stefano Leonardi, Rebecca Reiffenhäuser

For Round-Robin we show that all of its pure Nash equilibria induce allocations that are EF1 with respect to the underlying true values, while for the algorithm of Plaut and Roughgarden we show that the corresponding allocations not only are EFX but also satisfy maximin share fairness, something that is not true for this algorithm in the non-strategic setting!

Fairness

Bilateral Trade: A Regret Minimization Perspective

no code implementations8 Sep 2021 Nicolò Cesa-Bianchi, Tommaso Cesari, Roberto Colomboni, Federico Fusco, Stefano Leonardi

In this paper, we cast the bilateral trade problem in a regret minimization framework over $T$ rounds of seller/buyer interactions, with no prior knowledge on their private valuations.

Stochastic Bandits for Multi-platform Budget Optimization in Online Advertising

no code implementations16 Mar 2021 Vashist Avadhanula, Riccardo Colini-Baldeschi, Stefano Leonardi, Karthik Abinav Sankararaman, Okke Schrijvers

We modify the algorithm proposed in Badanidiyuru \emph{et al.,} to extend it to the case of multiple platforms to obtain an algorithm for both the discrete and continuous bid-spaces.

Flow Time Scheduling with Uncertain Processing Time

no code implementations9 Mar 2021 Yossi Azar, Stefano Leonardi, Noam Touitou

We consider the problem of online scheduling on a single machine in order to minimize weighted flow time.

Data Structures and Algorithms

Submodular Maximization subject to a Knapsack Constraint: Combinatorial Algorithms with Near-optimal Adaptive Complexity

no code implementations16 Feb 2021 Georgios Amanatidis, Federico Fusco, Philip Lazos, Stefano Leonardi, Alberto Marchetti Spaccamela, Rebecca Reiffenhäuser

Submodular maximization is a classic algorithmic problem with multiple applications in data mining and machine learning; there, the growing need to deal with massive instances motivates the design of algorithms balancing the quality of the solution with applicability.

A Regret Analysis of Bilateral Trade

no code implementations16 Feb 2021 Nicolò Cesa-Bianchi, Tommaso Cesari, Roberto Colomboni, Federico Fusco, Stefano Leonardi

Despite the simplicity of this problem, a classical result by Myerson and Satterthwaite (1983) affirms the impossibility of designing a mechanism which is simultaneously efficient, incentive compatible, individually rational, and budget balanced.

Fast Adaptive Non-Monotone Submodular Maximization Subject to a Knapsack Constraint

no code implementations NeurIPS 2020 Georgios Amanatidis, Federico Fusco, Philip Lazos, Stefano Leonardi, Rebecca Reiffenhäuser

Constrained submodular maximization problems encompass a wide variety of applications, including personalized recommendation, team formation, and revenue maximization via viral marketing.

Marketing

Algorithms for Hiring and Outsourcing in the Online Labor Market

no code implementations16 Feb 2020 Aris Anagnostopoulos, Carlos Castillo, Adriano Fazzone, Stefano Leonardi, Evimaria Terzi

In this paper, we provide algorithms for outsourcing and hiring workers in a general setting, where workers form a team and contribute different skills to perform a task.

Algorithms for Fair Team Formation in Online Labour Marketplaces

no code implementations14 Feb 2020 Giorgio Barnabò, Adriano Fazzone, Stefano Leonardi, Chris Schwiegelshohn

In this short paper, we define the Fair Team Formation problem in the following way: given an online labour marketplace where each worker possesses one or more skills, and where all workers are divided into two or more not overlapping classes (for examples, men and women), we want to design an algorithm that is able to find a team with all the skills needed to complete a given task, and that has the same number of people from all classes.

Fairness

Community Detection on Evolving Graphs

no code implementations NeurIPS 2016 Aris Anagnostopoulos, Jakub Łącki, Silvio Lattanzi, Stefano Leonardi, Mohammad Mahdian

In many of these applications, the input graph evolves over time in a continual and decentralized manner, and, to maintain a good clustering, the clustering algorithm needs to repeatedly probe the graph.

Clustering Community Detection +3

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