5 Search Results for "Deng, Xiaotie"


Document
APPROX
Scheduling Splittable Jobs on Configurable Machines

Authors: Matthew Casey, Rajmohan Rajaraman, David Stalfa, and Cheng Tan

Published in: LIPIcs, Volume 317, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2024)


Abstract
Motivated by modern architectures allowing for the partitioning of a GPU into hardware separated instances, we initiate the study of scheduling splittable jobs on configurable machines. We consider machines that can be configured into smaller instances, which we call blocks, in multiple ways, each of which is referred to as a configuration. We introduce the Configurable Machine Scheduling (cms) problem, where we are given n jobs and a set C of configurations. A schedule consists of a set of machines, each assigned some configuration in C with each block in the configuration assigned to process one job. The amount of a job’s demand that is satisfied by a block is given by an arbitrary function of the job and block. The objective is to construct a schedule using as few machines as possible. We provide a tight logarithmic factor approximation algorithm for this problem in the general setting, a factor (3 + ε) approximation algorithm for arbitrary ε > 0 when there are O(1) input configurations, and a polynomial time approximation scheme when both the number and size of configurations are O(1). Finally, we utilize a technique for finding conic integer combinations in fixed dimension to develop an optimal polynomial time algorithm in the case with O(1) jobs, O(1) blocks, and every configuration up to a given size.

Cite as

Matthew Casey, Rajmohan Rajaraman, David Stalfa, and Cheng Tan. Scheduling Splittable Jobs on Configurable Machines. In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 317, pp. 22:1-22:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)


Copy BibTex To Clipboard

@InProceedings{casey_et_al:LIPIcs.APPROX/RANDOM.2024.22,
  author =	{Casey, Matthew and Rajaraman, Rajmohan and Stalfa, David and Tan, Cheng},
  title =	{{Scheduling Splittable Jobs on Configurable Machines}},
  booktitle =	{Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2024)},
  pages =	{22:1--22:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-348-5},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{317},
  editor =	{Kumar, Amit and Ron-Zewi, Noga},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.APPROX/RANDOM.2024.22},
  URN =		{urn:nbn:de:0030-drops-210157},
  doi =		{10.4230/LIPIcs.APPROX/RANDOM.2024.22},
  annote =	{Keywords: Scheduling algorithms, Approximation algorithms, Configurable machines, Splittable jobs, Linear programming}
}
Document
Track A: Algorithms, Complexity and Games
Lipschitz Continuous Allocations for Optimization Games

Authors: Soh Kumabe and Yuichi Yoshida

Published in: LIPIcs, Volume 297, 51st International Colloquium on Automata, Languages, and Programming (ICALP 2024)


Abstract
In cooperative game theory, the primary focus is the equitable allocation of payoffs or costs among agents. However, in the practical applications of cooperative games, accurately representing games is challenging. In such cases, using an allocation method sensitive to small perturbations in the game can lead to various problems, including dissatisfaction among agents and the potential for manipulation by agents seeking to maximize their own benefits. Therefore, the allocation method must be robust against game perturbations. In this study, we explore optimization games, in which the value of the characteristic function is provided as the optimal value of an optimization problem. To assess the robustness of the allocation methods, we use the Lipschitz constant, which quantifies the extent of change in the allocation vector in response to a unit perturbation in the weight vector of the underlying problem. Thereafter, we provide an algorithm for the matching game that returns an allocation belonging to the (1/2-ε)-approximate core with Lipschitz constant O(ε^{-1}). Additionally, we provide an algorithm for a minimum spanning tree game that returns an allocation belonging to the 4-approximate core with a constant Lipschitz constant. The Shapley value is a popular allocation that satisfies several desirable properties. Therefore, we investigate the robustness of the Shapley value. We demonstrate that the Lipschitz constant of the Shapley value for the minimum spanning tree is constant, whereas that for the matching game is Ω(log n), where n denotes the number of vertices.

Cite as

Soh Kumabe and Yuichi Yoshida. Lipschitz Continuous Allocations for Optimization Games. In 51st International Colloquium on Automata, Languages, and Programming (ICALP 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 297, pp. 102:1-102:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)


Copy BibTex To Clipboard

@InProceedings{kumabe_et_al:LIPIcs.ICALP.2024.102,
  author =	{Kumabe, Soh and Yoshida, Yuichi},
  title =	{{Lipschitz Continuous Allocations for Optimization Games}},
  booktitle =	{51st International Colloquium on Automata, Languages, and Programming (ICALP 2024)},
  pages =	{102:1--102:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-322-5},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{297},
  editor =	{Bringmann, Karl and Grohe, Martin and Puppis, Gabriele and Svensson, Ola},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2024.102},
  URN =		{urn:nbn:de:0030-drops-202456},
  doi =		{10.4230/LIPIcs.ICALP.2024.102},
  annote =	{Keywords: Cooperative Games, Lipschitz Continuity}
}
Document
Consensus Division in an Arbitrary Ratio

Authors: Paul Goldberg and Jiawei Li

Published in: LIPIcs, Volume 251, 14th Innovations in Theoretical Computer Science Conference (ITCS 2023)


Abstract
We consider the problem of partitioning a line segment into two subsets, so that n finite measures all have the same ratio of values for the subsets. Letting α ∈ [0,1] denote the desired ratio, this generalises the PPA-complete consensus-halving problem, in which α = 1/2. Stromquist and Woodall [Stromquist and Woodall, 1985] showed that for any α, there exists a solution using 2n cuts of the segment. They also showed that if α is irrational, that upper bound is almost optimal. In this work, we elaborate the bounds for rational values α. For α = 𝓁/k, we show a lower bound of (k-1)/k ⋅ 2n - O(1) cuts; we also obtain almost matching upper bounds for a large subset of rational α. On the computational side, we explore its dependence on the number of cuts available. More specifically, 1) when using the minimal number of cuts for each instance is required, the problem is NP-hard for any α; 2) for a large subset of rational α = 𝓁/k, when (k-1)/k ⋅ 2n cuts are available, the problem is in PPA-k under Turing reduction; 3) when 2n cuts are allowed, the problem belongs to PPA for any α; more generally, the problem belong to PPA-p for any prime p if 2(p-1)⋅⌈p/2⌉/⌊p/2⌋ ⋅ n cuts are available.

Cite as

Paul Goldberg and Jiawei Li. Consensus Division in an Arbitrary Ratio. In 14th Innovations in Theoretical Computer Science Conference (ITCS 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 251, pp. 57:1-57:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


Copy BibTex To Clipboard

@InProceedings{goldberg_et_al:LIPIcs.ITCS.2023.57,
  author =	{Goldberg, Paul and Li, Jiawei},
  title =	{{Consensus Division in an Arbitrary Ratio}},
  booktitle =	{14th Innovations in Theoretical Computer Science Conference (ITCS 2023)},
  pages =	{57:1--57:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-263-1},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{251},
  editor =	{Tauman Kalai, Yael},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ITCS.2023.57},
  URN =		{urn:nbn:de:0030-drops-175606},
  doi =		{10.4230/LIPIcs.ITCS.2023.57},
  annote =	{Keywords: Consensus Halving, TFNP, PPA-k, Necklace Splitting}
}
Document
Smoothed and Average-Case Approximation Ratios of Mechanisms: Beyond the Worst-Case Analysis

Authors: Xiaotie Deng, Yansong Gao, and Jie Zhang

Published in: LIPIcs, Volume 83, 42nd International Symposium on Mathematical Foundations of Computer Science (MFCS 2017)


Abstract
The approximation ratio has become one of the dominant measures in mechanism design problems. In light of analysis of algorithms, we define the smoothed approximation ratio to compare the performance of the optimal mechanism and a truthful mechanism when the inputs are subject to random perturbations of the worst-case inputs, and define the average-case approximation ratio to compare the performance of these two mechanisms when the inputs follow a distribution. For the one-sided matching problem, Filos-Ratsikas et al. [2014] show that, amongst all truthful mechanisms, random priority achieves the tight approximation ratio bound of Theta(sqrt{n}). We prove that, despite of this worst-case bound, random priority has a constant smoothed approximation ratio. This is, to our limited knowledge, the first work that asymptotically differentiates the smoothed approximation ratio from the worst-case approximation ratio for mechanism design problems. For the average-case, we show that our approximation ratio can be improved to 1+e. These results partially explain why random priority has been successfully used in practice, although in the worst case the optimal social welfare is Theta(sqrt{n}) times of what random priority achieves. These results also pave the way for further studies of smoothed and average-case analysis for approximate mechanism design problems, beyond the worst-case analysis.

Cite as

Xiaotie Deng, Yansong Gao, and Jie Zhang. Smoothed and Average-Case Approximation Ratios of Mechanisms: Beyond the Worst-Case Analysis. In 42nd International Symposium on Mathematical Foundations of Computer Science (MFCS 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 83, pp. 16:1-16:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)


Copy BibTex To Clipboard

@InProceedings{deng_et_al:LIPIcs.MFCS.2017.16,
  author =	{Deng, Xiaotie and Gao, Yansong and Zhang, Jie},
  title =	{{Smoothed and Average-Case Approximation Ratios of Mechanisms: Beyond the Worst-Case Analysis}},
  booktitle =	{42nd International Symposium on Mathematical Foundations of Computer Science (MFCS 2017)},
  pages =	{16:1--16:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-046-0},
  ISSN =	{1868-8969},
  year =	{2017},
  volume =	{83},
  editor =	{Larsen, Kim G. and Bodlaender, Hans L. and Raskin, Jean-Francois},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.MFCS.2017.16},
  URN =		{urn:nbn:de:0030-drops-80936},
  doi =		{10.4230/LIPIcs.MFCS.2017.16},
  annote =	{Keywords: mechanism design, approximation ratio, smoothed analysis, average-case analysis}
}
Document
Understanding PPA-Completeness

Authors: Xiaotie Deng, Jack R. Edmonds, Zhe Feng, Zhengyang Liu, Qi Qi, and Zeying Xu

Published in: LIPIcs, Volume 50, 31st Conference on Computational Complexity (CCC 2016)


Abstract
We consider the problem of finding a fully colored base triangle on the 2-dimensional Möbius band under the standard boundary condition, proving it to be PPA-complete. The proof is based on a construction for the DPZP problem, that of finding a zero point under a discrete version of continuity condition. It further derives PPA-completeness for versions on the Möbius band of other related discrete fixed point type problems, and a special version of the Tucker problem, finding an edge such that if the value of one end vertex is x, the other is -x, given a special anti-symmetry boundary condition. More generally, this applies to other non-orientable spaces, including the projective plane and the Klein bottle. However, since those models have a closed boundary, we rely on a version of the PPA that states it as to find another fixed point giving a fixed point. This model also makes it presentationally simple for an extension to a high dimensional discrete fixed point problem on a non-orientable (nearly) hyper-grid with a constant side length.

Cite as

Xiaotie Deng, Jack R. Edmonds, Zhe Feng, Zhengyang Liu, Qi Qi, and Zeying Xu. Understanding PPA-Completeness. In 31st Conference on Computational Complexity (CCC 2016). Leibniz International Proceedings in Informatics (LIPIcs), Volume 50, pp. 23:1-23:25, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)


Copy BibTex To Clipboard

@InProceedings{deng_et_al:LIPIcs.CCC.2016.23,
  author =	{Deng, Xiaotie and Edmonds, Jack R. and Feng, Zhe and Liu, Zhengyang and Qi, Qi and Xu, Zeying},
  title =	{{Understanding PPA-Completeness}},
  booktitle =	{31st Conference on Computational Complexity (CCC 2016)},
  pages =	{23:1--23:25},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-008-8},
  ISSN =	{1868-8969},
  year =	{2016},
  volume =	{50},
  editor =	{Raz, Ran},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CCC.2016.23},
  URN =		{urn:nbn:de:0030-drops-58310},
  doi =		{10.4230/LIPIcs.CCC.2016.23},
  annote =	{Keywords: Fixed Point Computation, PPA-Completeness}
}
  • Refine by Author
  • 2 Deng, Xiaotie
  • 1 Casey, Matthew
  • 1 Edmonds, Jack R.
  • 1 Feng, Zhe
  • 1 Gao, Yansong
  • Show More...

  • Refine by Classification
  • 1 Mathematics of computing → Approximation algorithms
  • 1 Theory of computation → Problems, reductions and completeness
  • 1 Theory of computation → Scheduling algorithms

  • Refine by Keyword
  • 1 Approximation algorithms
  • 1 Configurable machines
  • 1 Consensus Halving
  • 1 Cooperative Games
  • 1 Fixed Point Computation
  • Show More...

  • Refine by Type
  • 5 document

  • Refine by Publication Year
  • 2 2024
  • 1 2016
  • 1 2017
  • 1 2023

Questions / Remarks / Feedback
X

Feedback for Dagstuhl Publishing


Thanks for your feedback!

Feedback submitted

Could not send message

Please try again later or send an E-mail