New Paper at AAAI 2022 01 Dec 2021
Our paper ''Maximizing Nash Social Welfare in 2-Value Instances'' (by Hannaneh Akrami, Bhaskar Ray Chaudhury, Martin Hoefer, Kurt Mehlhorn, Marco Schmalhofer, Golnoosh Shahkarami, Giovanna Varricchio, Quentin Vermande, Ernest van Wijland) was accepted at the 36th AAAI Conference on Artificial Intelligence (AAAI 2022), one of the two international top-conferences in artificial intelligence.
New Paper in Journal of Artificial Intelligence Research 26 Nov 2021
In our paper ''Fair Division of Indivisible Goods for a Class of Concave Valuations'' (by Bhaskar Ray Chaudhury, Yun Kuen Cheung, Jugal Garg, Naveen Garg, Martin Hoefer, Kurt Mehlhorn) we study approximation algorithms for fair allocation of a set of indivisible goods to a set of agents. Our algorithm computes a near-optimal allocation in terms of the geometric mean (also termed Nash social welfare) of agent valuations. In addition, the allocation satisfies approximate versions of envy-freeness, a standard fairness concept in the literature. Our results unify and extend existing techniques for approximating Nash social welfare for additive valuations to a more general, concave and non-separable class of valuation functions. The paper has been accepted for publication in Journal of Artificial Intelligence Research, a top journal in artificial intelligence.
New Paper in Mathematics of Operations Research 08 Sep 2021
In our paper ''Algorithms for Persuasion with Limited Communication'' (by Ronen Gradwohl, Niklas Hahn, Martin Hoefer, Rann Smorodinsky) we study the problem faced by a recommendation engine (e.g., a website for hotel booking or travel) that wants to persuade a user with a recommendation. We analyze restrictions on the signal space such that there are more potential actions by the user than signals that can be issued for recommendation. For symmetric instances, when a priori all actions have similar profits, we characterize and design efficient algorithms for optimal recommendation schemes for the engine. In a subclass of instances, where profits are independent among actions, we obtain an algorithm that computes a near-optimal scheme. The paper has been accepted for publication in Mathematics of Operations Research, a leading journal in operations research.
Tutorial on Algorithms and Information Design at SAGT 2021 27 Aug 2021
New Paper at SAGT 2021 29 Jun 2021
Our paper ''When Dividing Mixed Manna is Easier than Dividing Goods: Competitive Equilibria with a Constant Number of Chores'' (by Jugal Garg, Martin Hoefer, Peter McGlaughlin, Marco Schmalhofer) was accepted at the 14th Int. Symposium on Algorithmic Game Theory (SAGT 2021).
New Paper at IJCAI 2021 29 Apr 2021
Our paper ''Stochastic Probing with Increasing Precision'' (by Martin Hoefer, Kevin Schewior, Daniel Schmand) was accepted at the 30th Int. Joint Conference on Artificial Intelligence (IJCAI 2021), one of the two international top-conferences in artificial intelligence.
New Paper in American Economic Journal: Microeconomics 17 Mar 2021
In our paper ''Reaping the Informational Surplus in Bayesian Persuasion'' (by Ronen Gradwohl, Niklas Hahn, Martin Hoefer, Rann Smorodinsky) we study a competitive scenario, in which several experts with knowledge about the state of the world want to influence the choice of a decision maker (e.g., consultants/lobbyists try to influence policy decisions of the government). Even if there is only slight uncertainty for each expert about the interests of other experts, then the decision maker can extract the full informational surplus -- by restricting to listen only to one expert, the emerging competition motivates them to reveal all information about the state of the world. The paper has been accepted for publication in American Economic Journal: Microeconomics, a top-journal in economics.
Daniel Schmand moves to University of Bremen 05 Feb 2021
Welcome 01 Feb 2021
We welcome Tim Koglin as a new member of our group.
WINE 2020 Live Stream 26 Nov 2020
The 16th Conf. Web and Internet Economics (WINE 2020), one of the main events in economics and computation, is happening virtually Dec 7-11, 2020. There will be a free live stream on YouTube with all invited and contributed talks. All talks are scheduled within a (Europe-friendly) time window from 8am to 5pm CET.
New Paper at ITCS 2021 2 Nov 2020
Our paper ''Algorithmic Persuasion with Evidence'' (by Martin Hoefer, Pasin Manurangsi, Alexandros Psomas) was accepted at the 12th Int. Conf. Innovations in Theoretical Computer Science (ITCS 2021), a top-conference in theory of computing.
Welcome 1 Nov 2020
We welcome Giovanna Varricchio as a new member of our group.
Welcome 1 Oct 2020
We welcome Lisa Wilhelmi as a new member of our group.
New Paper at SODA 2021 30 Sep 2020
Our paper ''Algorithms for Persuasion with Limited Communication'' (by Ronen Gradwohl, Niklas Hahn, Martin Hoefer, Rann Smorodinsky) was accepted at the 31st Symposium on Discrete Algorithms (SODA 2021), the international top-conference in design and analysis of algorithms.
New Paper in Networks 29 Sep 2020
In our paper ''Packing Returning Secretaries'' (by Martin Hoefer, Lisa Wilhelmi) we analyze extensions of the classic secretary problem and relax the assumption that the decision for a specific element must be made instantaneously. Our results are approximation guarantees for a wide class of combinatorial packing problems, such as knapsack, matching or independent set. Moreover, we are interested in scenarios where the decision for an element can be postponed, with the goal of selecting an optimal set of elements with the minimum number of postponements. The paper has been accepted for publication in Networks.
New Paper at COLT 2020 26 May 2020
In the new paper ''A Nearly Optimal Variant of the Perceptron Algorithm for the Uniform Distribution on the Unit Sphere'', Marco Schmalhofer shows that a simple variant of the classic perceptron algorithm provides near-optimal guarantees for PAC-learning of halfspaces, where examples are drawn uniformly at random on the hypersphere. The paper was accepted at the 33rd Annual Conference on Learning Theory (COLT 2020), the international top-conference in learning theory.
Two Papers at EC 2020 6 May 2020
Two papers from our group were accepted at the 21st ACM Conference on Economics and Computation (EC 2020), the international top-conference at the intersection of computer science and economics:
- The Secretary Recommendation Problem
(by Niklas Hahn, Martin Hoefer, Rann Smorodinsky)
- Portfolio Compression in Financial Networks: Incentives and Systemic Risk
(by Steffen Schuldenzucker, Sven Seuken)
DFG Research Group 29 Apr 2020
The German Research Foundation grants funding for a new research group on Algorithms, Dynamics, and Information Flow in Networks. The group is headed by Martin Hoefer, the participating PIs are Petra Berenbrink (Hamburg), Nils Bertschinger, Amin Coja Oghlan, Ulrich Meyer (Frankfurt) and Tobias Friedrich (HPI/Potsdam). The goals are to advance our understanding of dynamic processes on networks and their relation to efficient algorithms, e.g., in the analysis of spreading processes, distributed network algorithms, network generation models, as well as application domains such as financial markets.
New Paper at IJCAI 2020 21 Apr 2020
Our paper ''Prophet Inequalities for Bayesian Persuasion'' (by Niklas Hahn, Martin Hoefer, Rann Smorodinsky) was accepted at the 29th Int. Joint Conference on Artificial Intelligence (IJCAI 2020), one of the two international top-conferences in artificial intelligence.
Visitor 01 Mar 2020
Kevin Schewior is visiting our group Mar 9-13.
DFG Grant 14 Feb 2020
In a our new three-year project Algorithms for Fair Allocation of Indivisible Goods funded by the German Research Foundation, we study algorithmic problems for fair assignment of indivisble goods, which arise, e.g., when assigning students to schools, splitting an inheritance, sharing rooms in an appartment, etc. Jugal Garg from the University of Illinois at Urbana-Champaign collaborates with us as a Mercator Fellow.
Welcome 16 Jan 2020
We welcome Marco Schmalhofer as a new member of our group.
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