6 Search Results for "Gao, Jie"


Document
RANDOM
Evaluating Stability in Massive Social Networks: Efficient Streaming Algorithms for Structural Balance

Authors: Vikrant Ashvinkumar, Sepehr Assadi, Chengyuan Deng, Jie Gao, and Chen Wang

Published in: LIPIcs, Volume 275, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2023)


Abstract
Structural balance theory studies stability in networks. Given a n-vertex complete graph G = (V,E) whose edges are labeled positive or negative, the graph is considered balanced if every triangle either consists of three positive edges (three mutual "friends"), or one positive edge and two negative edges (two "friends" with a common "enemy"). From a computational perspective, structural balance turns out to be a special case of correlation clustering with the number of clusters at most two. The two main algorithmic problems of interest are: (i) detecting whether a given graph is balanced, or (ii) finding a partition that approximates the frustration index, i.e., the minimum number of edge flips that turn the graph balanced. We study these problems in the streaming model where edges are given one by one and focus on memory efficiency. We provide randomized single-pass algorithms for: (i) determining whether an input graph is balanced with O(log n) memory, and (ii) finding a partition that induces a (1 + ε)-approximation to the frustration index with O(n ⋅ polylog(n)) memory. We further provide several new lower bounds, complementing different aspects of our algorithms such as the need for randomization or approximation. To obtain our main results, we develop a method using pseudorandom generators (PRGs) to sample edges between independently-chosen vertices in graph streaming. Furthermore, our algorithm that approximates the frustration index improves the running time of the state-of-the-art correlation clustering with two clusters (Giotis-Guruswami algorithm [SODA 2006]) from n^O(1/ε²) to O(n²log³n/ε² + n log n ⋅ (1/ε)^O(1/ε⁴)) time for (1+ε)-approximation. These results may be of independent interest.

Cite as

Vikrant Ashvinkumar, Sepehr Assadi, Chengyuan Deng, Jie Gao, and Chen Wang. Evaluating Stability in Massive Social Networks: Efficient Streaming Algorithms for Structural Balance. In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 275, pp. 58:1-58:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


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@InProceedings{ashvinkumar_et_al:LIPIcs.APPROX/RANDOM.2023.58,
  author =	{Ashvinkumar, Vikrant and Assadi, Sepehr and Deng, Chengyuan and Gao, Jie and Wang, Chen},
  title =	{{Evaluating Stability in Massive Social Networks: Efficient Streaming Algorithms for Structural Balance}},
  booktitle =	{Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2023)},
  pages =	{58:1--58:23},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-296-9},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{275},
  editor =	{Megow, Nicole and Smith, Adam},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.APPROX/RANDOM.2023.58},
  URN =		{urn:nbn:de:0030-drops-188830},
  doi =		{10.4230/LIPIcs.APPROX/RANDOM.2023.58},
  annote =	{Keywords: Streaming algorithms, structural balance, pseudo-randomness generator}
}
Document
Completeness Matters: Towards Efficient Caching in Tree-Based Synchronous Backtracking Search for DCOPs

Authors: Jie Wang, Dingding Chen, Ziyu Chen, Xiangshuang Liu, and Junsong Gao

Published in: LIPIcs, Volume 235, 28th International Conference on Principles and Practice of Constraint Programming (CP 2022)


Abstract
Tree-based backtracking search is an important technique to solve Distributed Constraint optimization Problems (DCOPs), where agents cooperatively exhaust the search space by branching on each variable to divide subproblems and reporting the results to their parent after solving each subproblem. Therefore, effectively reusing the historical search results can avoid unnecessary resolutions and substantially reduce the overall overhead. However, the existing caching schemes for asynchronous algorithms cannot be applied directly to synchronous ones, in the sense that child agent reports the lower and upper bound rather than the precise cost of exploration. In addition, the existing caching scheme for synchronous algorithms has the shortcomings of incompleteness and low cache utilization. Therefore, we propose a new caching scheme for tree-based synchronous backtracking search, named Retention Scheme (RS). It utilizes the upper bounds of subproblems which avoid the reuse of suboptimal solutions to ensure the completeness, and deploys a fine-grained cache information unit targeted at each child agent to improve the cache-hit rate. Furthermore, we introduce two new cache replacement schemes to further improve performance when the memory is limited. Finally, we theoretically prove the completeness of our method and empirically show its superiority.

Cite as

Jie Wang, Dingding Chen, Ziyu Chen, Xiangshuang Liu, and Junsong Gao. Completeness Matters: Towards Efficient Caching in Tree-Based Synchronous Backtracking Search for DCOPs. In 28th International Conference on Principles and Practice of Constraint Programming (CP 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 235, pp. 39:1-39:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)


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@InProceedings{wang_et_al:LIPIcs.CP.2022.39,
  author =	{Wang, Jie and Chen, Dingding and Chen, Ziyu and Liu, Xiangshuang and Gao, Junsong},
  title =	{{Completeness Matters: Towards Efficient Caching in Tree-Based Synchronous Backtracking Search for DCOPs}},
  booktitle =	{28th International Conference on Principles and Practice of Constraint Programming (CP 2022)},
  pages =	{39:1--39:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-240-2},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{235},
  editor =	{Solnon, Christine},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2022.39},
  URN =		{urn:nbn:de:0030-drops-166685},
  doi =		{10.4230/LIPIcs.CP.2022.39},
  annote =	{Keywords: DCOP, Cache, Any-space Algorithms, Complete Search Algorithms}
}
Document
On Cyclic Solutions to the Min-Max Latency Multi-Robot Patrolling Problem

Authors: Peyman Afshani, Mark de Berg, Kevin Buchin, Jie Gao, Maarten Löffler, Amir Nayyeri, Benjamin Raichel, Rik Sarkar, Haotian Wang, and Hao-Tsung Yang

Published in: LIPIcs, Volume 224, 38th International Symposium on Computational Geometry (SoCG 2022)


Abstract
We consider the following surveillance problem: Given a set P of n sites in a metric space and a set R of k robots with the same maximum speed, compute a patrol schedule of minimum latency for the robots. Here a patrol schedule specifies for each robot an infinite sequence of sites to visit (in the given order) and the latency L of a schedule is the maximum latency of any site, where the latency of a site s is the supremum of the lengths of the time intervals between consecutive visits to s. When k = 1 the problem is equivalent to the travelling salesman problem (TSP) and thus it is NP-hard. For k ≥ 2 (which is the version we are interested in) the problem becomes even more challenging; for example, it is not even clear if the decision version of the problem is decidable, in particular in the Euclidean case. We have two main results. We consider cyclic solutions in which the set of sites must be partitioned into 𝓁 groups, for some 𝓁 ≤ k, and each group is assigned a subset of the robots that move along the travelling salesman tour of the group at equal distance from each other. Our first main result is that approximating the optimal latency of the class of cyclic solutions can be reduced to approximating the optimal travelling salesman tour on some input, with only a 1+ε factor loss in the approximation factor and an O((k/ε) ^k) factor loss in the runtime, for any ε > 0. Our second main result shows that an optimal cyclic solution is a 2(1-1/k)-approximation of the overall optimal solution. Note that for k = 2 this implies that an optimal cyclic solution is optimal overall. We conjecture that this is true for k ≥ 3 as well. The results have a number of consequences. For the Euclidean version of the problem, for instance, combining our results with known results on Euclidean TSP, yields a PTAS for approximating an optimal cyclic solution, and it yields a (2(1-1/k)+ε)-approximation of the optimal unrestricted (not necessarily cyclic) solution. If the conjecture mentioned above is true, then our algorithm is actually a PTAS for the general problem in the Euclidean setting. Similar results can be obtained by combining our results with other known TSP algorithms in non-Euclidean metrics.

Cite as

Peyman Afshani, Mark de Berg, Kevin Buchin, Jie Gao, Maarten Löffler, Amir Nayyeri, Benjamin Raichel, Rik Sarkar, Haotian Wang, and Hao-Tsung Yang. On Cyclic Solutions to the Min-Max Latency Multi-Robot Patrolling Problem. In 38th International Symposium on Computational Geometry (SoCG 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 224, pp. 2:1-2:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)


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@InProceedings{afshani_et_al:LIPIcs.SoCG.2022.2,
  author =	{Afshani, Peyman and de Berg, Mark and Buchin, Kevin and Gao, Jie and L\"{o}ffler, Maarten and Nayyeri, Amir and Raichel, Benjamin and Sarkar, Rik and Wang, Haotian and Yang, Hao-Tsung},
  title =	{{On Cyclic Solutions to the Min-Max Latency Multi-Robot Patrolling Problem}},
  booktitle =	{38th International Symposium on Computational Geometry (SoCG 2022)},
  pages =	{2:1--2:14},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-227-3},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{224},
  editor =	{Goaoc, Xavier and Kerber, Michael},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.SoCG.2022.2},
  URN =		{urn:nbn:de:0030-drops-160109},
  doi =		{10.4230/LIPIcs.SoCG.2022.2},
  annote =	{Keywords: Approximation, Motion Planning, Scheduling}
}
Document
Cutting Polygons into Small Pieces with Chords: Laser-Based Localization

Authors: Esther M. Arkin, Rathish Das, Jie Gao, Mayank Goswami, Joseph S. B. Mitchell, Valentin Polishchuk, and Csaba D. Tóth

Published in: LIPIcs, Volume 173, 28th Annual European Symposium on Algorithms (ESA 2020)


Abstract
Motivated by indoor localization by tripwire lasers, we study the problem of cutting a polygon into small-size pieces, using the chords of the polygon. Several versions are considered, depending on the definition of the "size" of a piece. In particular, we consider the area, the diameter, and the radius of the largest inscribed circle as a measure of the size of a piece. We also consider different objectives, either minimizing the maximum size of a piece for a given number of chords, or minimizing the number of chords that achieve a given size threshold for the pieces. We give hardness results for polygons with holes and approximation algorithms for multiple variants of the problem.

Cite as

Esther M. Arkin, Rathish Das, Jie Gao, Mayank Goswami, Joseph S. B. Mitchell, Valentin Polishchuk, and Csaba D. Tóth. Cutting Polygons into Small Pieces with Chords: Laser-Based Localization. In 28th Annual European Symposium on Algorithms (ESA 2020). Leibniz International Proceedings in Informatics (LIPIcs), Volume 173, pp. 7:1-7:23, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2020)


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@InProceedings{arkin_et_al:LIPIcs.ESA.2020.7,
  author =	{Arkin, Esther M. and Das, Rathish and Gao, Jie and Goswami, Mayank and Mitchell, Joseph S. B. and Polishchuk, Valentin and T\'{o}th, Csaba D.},
  title =	{{Cutting Polygons into Small Pieces with Chords: Laser-Based Localization}},
  booktitle =	{28th Annual European Symposium on Algorithms (ESA 2020)},
  pages =	{7:1--7:23},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-162-7},
  ISSN =	{1868-8969},
  year =	{2020},
  volume =	{173},
  editor =	{Grandoni, Fabrizio and Herman, Grzegorz and Sanders, Peter},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2020.7},
  URN =		{urn:nbn:de:0030-drops-128736},
  doi =		{10.4230/LIPIcs.ESA.2020.7},
  annote =	{Keywords: Polygon partition, Arrangements, Visibility, Localization}
}
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)


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@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-dev.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
Discovery of Sensor Network Layout using Connectivity Information

Authors: Jie Gao, Sol Lederer, and Yue Wang

Published in: Dagstuhl Seminar Proceedings, Volume 7151, Geometry in Sensor Networks (2007)


Abstract
We propose a distributed algorithm to discover and recover the layout of a large sensor network having a complex shape. As sensor network deployments grow large in size and become non-uniform, localization algorithms suffer from ``flip'' ambiguities---where a part of the network folds on top of another while keeping all edge length measurements preserved. We explore the high-order topological information in a sensor field to prevent incorrect flips and accurately recover the shape of the sensor network. We select landmarks on network boundaries with sufficient density, construct the landmark Voronoi diagram and its dual combinatorial Delaunay complex on these landmarks. The key insight is that when the landmarks are dense enough to capture the local geometric complexity, the combinatorial Delaunay complex is globally rigid and has a unique realization in the plane. An embedding by simply gluing the Delaunay triangles properly derives a faithful network layout, which consequently leads to a practical and sufficiently accurate localization algorithm. We prove the global rigidity of the combinatorial Delaunay complex in the case of a continuous geometric region. Simulation results on discrete networks show surprisingly good results, while multi-dimensional scaling and rubberband representation perform poorly or not at all in recovering the network layout. This is joint work with Sol Lederer and Yue Wang.

Cite as

Jie Gao, Sol Lederer, and Yue Wang. Discovery of Sensor Network Layout using Connectivity Information. In Geometry in Sensor Networks. Dagstuhl Seminar Proceedings, Volume 7151, pp. 1-14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2007)


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@InProceedings{gao_et_al:DagSemProc.07151.2,
  author =	{Gao, Jie and Lederer, Sol and Wang, Yue},
  title =	{{Discovery of Sensor Network Layout using Connectivity Information}},
  booktitle =	{Geometry in Sensor Networks},
  pages =	{1--14},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2007},
  volume =	{7151},
  editor =	{Subhash Suri and Roger Wattenhofer and Peter Widmayer},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/DagSemProc.07151.2},
  URN =		{urn:nbn:de:0030-drops-11149},
  doi =		{10.4230/DagSemProc.07151.2},
  annote =	{Keywords: Sensor Networks, Localization, Delaunay complex, Rigidity}
}
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