7 Search Results for "Papp, Pál András"

Document
Invited Talk
DOI: 10.4230/LIPIcs.SAND.2022.3
Networks, Dynamics, Algorithms, and Learning (Invited Talk)

Authors: Roger Wattenhofer

Published in: LIPIcs, Volume 221, 1st Symposium on Algorithmic Foundations of Dynamic Networks (SAND 2022)

Abstract
Networks are notoriously difficult to understand, and adding dynamics does not help. Can the current wonder weapon of computation (yes, machine learning) come to the rescue? Unfortunately, learning with networks is generally not well understood. "Neural network networks" (better and less confusingly known as graph neural networks) can learn simple graph patterns, but they are a far cry from their impressive machine learning cousins in the image- or the game-domain. In my opinion, the most astonishing graph neural networks are in fact dealing with dynamic networks: They simulate sand (the granular material, not the symposium) quite naturally. In my talk, I will discuss and compare different computational objects and paradigms: networks, dynamics, algorithms, and learning. What are the differences? And what can they learn from each other? In the technical part of the talk, I will present DropGNN, our new algorithm-inspired approach for handling graph neural networks. But mostly I will vent about misunderstandings and mistakes, and I will propose open questions, and new research directions. DropGNN is joint work with Pál András Papp, Karolis Martinkus, and Lukas Faber, published at NeurIPS, December 2021.
Cite as

Roger Wattenhofer. Networks, Dynamics, Algorithms, and Learning (Invited Talk). In 1st Symposium on Algorithmic Foundations of Dynamic Networks (SAND 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 221, p. 3:1, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{wattenhofer:LIPIcs.SAND.2022.3,
  author =	{Wattenhofer, Roger},
  title =	{{Networks, Dynamics, Algorithms, and Learning}},
  booktitle =	{1st Symposium on Algorithmic Foundations of Dynamic Networks (SAND 2022)},
  pages =	{3:1--3:1},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-224-2},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{221},
  editor =	{Aspnes, James and Michail, Othon},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.SAND.2022.3},
  URN =		{urn:nbn:de:0030-drops-159451},
  doi =		{10.4230/LIPIcs.SAND.2022.3},
  annote =	{Keywords: graph neural networks}
}
Document
DOI: 10.4230/LIPIcs.MFCS.2021.83
Stabilization Bounds for Influence Propagation from a Random Initial State

Authors: Pál András Papp and Roger Wattenhofer

Published in: LIPIcs, Volume 202, 46th International Symposium on Mathematical Foundations of Computer Science (MFCS 2021)

Abstract
We study the stabilization time of two common types of influence propagation. In majority processes, nodes in a graph want to switch to the most frequent state in their neighborhood, while in minority processes, nodes want to switch to the least frequent state in their neighborhood. We consider the sequential model of these processes, and assume that every node starts out from a uniform random state. We first show that if nodes change their state for any small improvement in the process, then stabilization can last for up to Θ(n²) steps in both cases. Furthermore, we also study the proportional switching case, when nodes only decide to change their state if they are in conflict with a (1+λ)/2 fraction of their neighbors, for some parameter λ ∈ (0,1). In this case, we show that if λ < 1/3, then there is a construction where stabilization can indeed last for Ω(n^{1+c}) steps for some constant c > 0. On the other hand, if λ > 1/2, we prove that the stabilization time of the processes is upper-bounded by O(n ⋅ log n).
Cite as

Pál András Papp and Roger Wattenhofer. Stabilization Bounds for Influence Propagation from a Random Initial State. In 46th International Symposium on Mathematical Foundations of Computer Science (MFCS 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 202, pp. 83:1-83:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{papp_et_al:LIPIcs.MFCS.2021.83,
  author =	{Papp, P\'{a}l Andr\'{a}s and Wattenhofer, Roger},
  title =	{{Stabilization Bounds for Influence Propagation from a Random Initial State}},
  booktitle =	{46th International Symposium on Mathematical Foundations of Computer Science (MFCS 2021)},
  pages =	{83:1--83:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-201-3},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{202},
  editor =	{Bonchi, Filippo and Puglisi, Simon J.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.MFCS.2021.83},
  URN =		{urn:nbn:de:0030-drops-145239},
  doi =		{10.4230/LIPIcs.MFCS.2021.83},
  annote =	{Keywords: Majority process, Minority process, Stabilization time, Random initialization, Asynchronous model}
}
Document
DOI: 10.4230/LIPIcs.ITCS.2021.52
Sequential Defaulting in Financial Networks

Authors: Pál András Papp and Roger Wattenhofer

Published in: LIPIcs, Volume 185, 12th Innovations in Theoretical Computer Science Conference (ITCS 2021)

Abstract
We consider financial networks, where banks are connected by contracts such as debts or credit default swaps. We study the clearing problem in these systems: we want to know which banks end up in a default, and what portion of their liabilities can these defaulting banks fulfill. We analyze these networks in a sequential model where banks announce their default one at a time, and the system evolves in a step-by-step manner. We first consider the reversible model of these systems, where banks may return from a default. We show that the stabilization time in this model can heavily depend on the ordering of announcements. However, we also show that there are systems where for any choice of ordering, the process lasts for an exponential number of steps before an eventual stabilization. We also show that finding the ordering with the smallest (or largest) number of banks ending up in default is an NP-hard problem. Furthermore, we prove that defaulting early can be an advantageous strategy for banks in some cases, and in general, finding the best time for a default announcement is NP-hard. Finally, we discuss how changing some properties of this setting affects the stabilization time of the process, and then use these techniques to devise a monotone model of the systems, which ensures that every network stabilizes eventually.
Cite as

Pál András Papp and Roger Wattenhofer. Sequential Defaulting in Financial Networks. In 12th Innovations in Theoretical Computer Science Conference (ITCS 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 185, pp. 52:1-52:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{papp_et_al:LIPIcs.ITCS.2021.52,
  author =	{Papp, P\'{a}l Andr\'{a}s and Wattenhofer, Roger},
  title =	{{Sequential Defaulting in Financial Networks}},
  booktitle =	{12th Innovations in Theoretical Computer Science Conference (ITCS 2021)},
  pages =	{52:1--52:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-177-1},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{185},
  editor =	{Lee, James R.},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2021.52},
  URN =		{urn:nbn:de:0030-drops-135919},
  doi =		{10.4230/LIPIcs.ITCS.2021.52},
  annote =	{Keywords: Financial Network, Sequential Defaulting, Credit Default Swap, Clearing Problem, Stabilization Time}
}
Document
Track A: Algorithms, Complexity and Games
DOI: 10.4230/LIPIcs.ICALP.2020.90
A General Stabilization Bound for Influence Propagation in Graphs

Authors: Pál András Papp and Roger Wattenhofer

Published in: LIPIcs, Volume 168, 47th International Colloquium on Automata, Languages, and Programming (ICALP 2020)

Abstract
We study the stabilization time of a wide class of processes on graphs, in which each node can only switch its state if it is motivated to do so by at least a (1+λ)/2 fraction of its neighbors, for some 0 < λ < 1. Two examples of such processes are well-studied dynamically changing colorings in graphs: in majority processes, nodes switch to the most frequent color in their neighborhood, while in minority processes, nodes switch to the least frequent color in their neighborhood. We describe a non-elementary function f(λ), and we show that in the sequential model, the worst-case stabilization time of these processes can completely be characterized by f(λ). More precisely, we prove that for any ε > 0, O(n^(1+f(λ)+ε)) is an upper bound on the stabilization time of any proportional majority/minority process, and we also show that there are graph constructions where stabilization indeed takes Ω(n^(1+f(λ)-ε)) steps.
Cite as

Pál András Papp and Roger Wattenhofer. A General Stabilization Bound for Influence Propagation in Graphs. In 47th International Colloquium on Automata, Languages, and Programming (ICALP 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 168, pp. 90:1-90:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{papp_et_al:LIPIcs.ICALP.2020.90,
  author =	{Papp, P\'{a}l Andr\'{a}s and Wattenhofer, Roger},
  title =	{{A General Stabilization Bound for Influence Propagation in Graphs}},
  booktitle =	{47th International Colloquium on Automata, Languages, and Programming (ICALP 2020)},
  pages =	{90:1--90:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-138-2},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{168},
  editor =	{Czumaj, Artur and Dawar, Anuj and Merelli, Emanuela},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2020.90},
  URN =		{urn:nbn:de:0030-drops-124978},
  doi =		{10.4230/LIPIcs.ICALP.2020.90},
  annote =	{Keywords: Minority process, Majority process}
}
Document
Track A: Algorithms, Complexity and Games
DOI: 10.4230/LIPIcs.ICALP.2020.91
Network-Aware Strategies in Financial Systems

Authors: Pál András Papp and Roger Wattenhofer

Published in: LIPIcs, Volume 168, 47th International Colloquium on Automata, Languages, and Programming (ICALP 2020)

Abstract
We study the incentives of banks in a financial network, where the network consists of debt contracts and credit default swaps (CDSs) between banks. One of the most important questions in such a system is the problem of deciding which of the banks are in default, and how much of their liabilities these banks can pay. We study the payoff and preferences of the banks in the different solutions to this problem. We also introduce a more refined model which allows assigning priorities to payment obligations; this provides a more expressive and realistic model of real-life financial systems, while it always ensures the existence of a solution. The main focus of the paper is an analysis of the actions that a single bank can execute in a financial system in order to influence the outcome to its advantage. We show that removing an incoming debt, or donating funds to another bank can result in a single new solution that is strictly more favorable to the acting bank. We also show that increasing the bank’s external funds or modifying the priorities of outgoing payments cannot introduce a more favorable new solution into the system, but may allow the bank to remove some unfavorable solutions, or to increase its recovery rate. Finally, we show how the actions of two banks in a simple financial system can result in classical game theoretic situations like the prisoner’s dilemma or the dollar auction, demonstrating the wide expressive capability of the financial system model.
Cite as

Pál András Papp and Roger Wattenhofer. Network-Aware Strategies in Financial Systems. In 47th International Colloquium on Automata, Languages, and Programming (ICALP 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 168, pp. 91:1-91:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)

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@InProceedings{papp_et_al:LIPIcs.ICALP.2020.91,
  author =	{Papp, P\'{a}l Andr\'{a}s and Wattenhofer, Roger},
  title =	{{Network-Aware Strategies in Financial Systems}},
  booktitle =	{47th International Colloquium on Automata, Languages, and Programming (ICALP 2020)},
  pages =	{91:1--91:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-138-2},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{168},
  editor =	{Czumaj, Artur and Dawar, Anuj and Merelli, Emanuela},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2020.91},
  URN =		{urn:nbn:de:0030-drops-124988},
  doi =		{10.4230/LIPIcs.ICALP.2020.91},
  annote =	{Keywords: Financial network, credit default swap, creditor priority, clearing problem, prisoner’s dilemma, dollar auction}
}
Document
DOI: 10.4230/LIPIcs.ISAAC.2019.43
Stabilization Time in Minority Processes

Authors: Pál András Papp and Roger Wattenhofer

Published in: LIPIcs, Volume 149, 30th International Symposium on Algorithms and Computation (ISAAC 2019)

Abstract
We analyze the stabilization time of minority processes in graphs. A minority process is a dynamically changing coloring, where each node repeatedly changes its color to the color which is least frequent in its neighborhood. First, we present a simple Omega(n^2) stabilization time lower bound in the sequential adversarial model. Our main contribution is a graph construction which proves a Omega(n^(2-epsilon)) stabilization time lower bound for any epsilon>0. This lower bound holds even if the order of nodes is chosen benevolently, not only in the sequential model, but also in any reasonable concurrent model of the process.
Cite as

Pál András Papp and Roger Wattenhofer. Stabilization Time in Minority Processes. In 30th International Symposium on Algorithms and Computation (ISAAC 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 149, pp. 43:1-43:19, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{papp_et_al:LIPIcs.ISAAC.2019.43,
  author =	{Papp, P\'{a}l Andr\'{a}s and Wattenhofer, Roger},
  title =	{{Stabilization Time in Minority Processes}},
  booktitle =	{30th International Symposium on Algorithms and Computation (ISAAC 2019)},
  pages =	{43:1--43:19},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-130-6},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{149},
  editor =	{Lu, Pinyan and Zhang, Guochuan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.ISAAC.2019.43},
  URN =		{urn:nbn:de:0030-drops-115393},
  doi =		{10.4230/LIPIcs.ISAAC.2019.43},
  annote =	{Keywords: Minority process, Benevolent model}
}
Document
DOI: 10.4230/LIPIcs.STACS.2019.54
Stabilization Time in Weighted Minority Processes

Authors: Pál András Papp and Roger Wattenhofer

Published in: LIPIcs, Volume 126, 36th International Symposium on Theoretical Aspects of Computer Science (STACS 2019)

Abstract
A minority process in a weighted graph is a dynamically changing coloring. Each node repeatedly changes its color in order to minimize the sum of weighted conflicts with its neighbors. We study the number of steps until such a process stabilizes. Our main contribution is an exponential lower bound on stabilization time. We first present a construction showing this bound in the adversarial sequential model, and then we show how to extend the construction to establish the same bound in the benevolent sequential model, as well as in any reasonable concurrent model. Furthermore, we show that the stabilization time of our construction remains exponential even for very strict switching conditions, namely, if a node only changes color when almost all (i.e., any specific fraction) of its neighbors have the same color. Our lower bound works in a wide range of settings, both for node-weighted and edge-weighted graphs, or if we restrict minority processes to the class of sparse graphs.
Cite as

Pál András Papp and Roger Wattenhofer. Stabilization Time in Weighted Minority Processes. In 36th International Symposium on Theoretical Aspects of Computer Science (STACS 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 126, pp. 54:1-54:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{papp_et_al:LIPIcs.STACS.2019.54,
  author =	{Papp, P\'{a}l Andr\'{a}s and Wattenhofer, Roger},
  title =	{{Stabilization Time in Weighted Minority Processes}},
  booktitle =	{36th International Symposium on Theoretical Aspects of Computer Science (STACS 2019)},
  pages =	{54:1--54:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-100-9},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{126},
  editor =	{Niedermeier, Rolf and Paul, Christophe},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.STACS.2019.54},
  URN =		{urn:nbn:de:0030-drops-102938},
  doi =		{10.4230/LIPIcs.STACS.2019.54},
  annote =	{Keywords: Minority process, Benevolent model}
}
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