3 Search Results for "Feng, Lu"


Document
Small Candidate Set for Translational Pattern Search

Authors: Ziyun Huang, Qilong Feng, Jianxin Wang, and Jinhui Xu

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


Abstract
In this paper, we study the following pattern search problem: Given a pair of point sets A and B in fixed dimensional space R^d, with |B| = n, |A| = m and n >= m, the pattern search problem is to find the translations T’s of A such that each of the identified translations induces a matching between T(A) and a subset B' of B with cost no more than some given threshold, where the cost is defined as the minimum bipartite matching cost of T(A) and B'. We present a novel algorithm to produce a small set of candidate translations for the pattern search problem. For any B' subseteq B with |B'| = |A|, there exists at least one translation T in the candidate set such that the minimum bipartite matching cost between T(A) and B' is no larger than (1+epsilon) times the minimum bipartite matching cost between A and B' under any translation (i.e., the optimal translational matching cost). We also show that there exists an alternative solution to this problem, which constructs a candidate set of size O(n log^2 n) in O(n log^2 n) time with high probability of success. As a by-product of our construction, we obtain a weak epsilon-net for hypercube ranges, which significantly improves the construction time and the size of the candidate set. Our technique can be applied to a number of applications, including the translational pattern matching problem.

Cite as

Ziyun Huang, Qilong Feng, Jianxin Wang, and Jinhui Xu. Small Candidate Set for Translational Pattern Search. In 30th International Symposium on Algorithms and Computation (ISAAC 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 149, pp. 26:1-26:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)


Copy BibTex To Clipboard

@InProceedings{huang_et_al:LIPIcs.ISAAC.2019.26,
  author =	{Huang, Ziyun and Feng, Qilong and Wang, Jianxin and Xu, Jinhui},
  title =	{{Small Candidate Set for Translational Pattern Search}},
  booktitle =	{30th International Symposium on Algorithms and Computation (ISAAC 2019)},
  pages =	{26:1--26:17},
  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.2019.26},
  URN =		{urn:nbn:de:0030-drops-115222},
  doi =		{10.4230/LIPIcs.ISAAC.2019.26},
  annote =	{Keywords: Bipartite matching, Alignment, Discretization, Approximate algorithm}
}
Document
Improved Algorithms for Clustering with Outliers

Authors: Qilong Feng, Zhen Zhang, Ziyun Huang, Jinhui Xu, and Jianxin Wang

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


Abstract
Clustering is a fundamental problem in unsupervised learning. In many real-world applications, the to-be-clustered data often contains various types of noises and thus needs to be removed from the learning process. To address this issue, we consider in this paper two variants of such clustering problems, called k-median with m outliers and k-means with m outliers. Existing techniques for both problems either incur relatively large approximation ratios or can only efficiently deal with a small number of outliers. In this paper, we present improved solution to each of them for the case where k is a fixed number and m could be quite large. Particularly, we gave the first PTAS for the k-median problem with outliers in Euclidean space R^d for possibly high m and d. Our algorithm runs in O(nd((1/epsilon)(k+m))^(k/epsilon)^O(1)) time, which considerably improves the previous result (with running time O(nd(m+k)^O(m+k) + (1/epsilon)k log n)^O(1))) given by [Feldman and Schulman, SODA 2012]. For the k-means with outliers problem, we introduce a (6+epsilon)-approximation algorithm for general metric space with running time O(n(beta (1/epsilon)(k+m))^k) for some constant beta>1. Our algorithm first uses the k-means++ technique to sample O((1/epsilon)(k+m)) points from input and then select the k centers from them. Compared to the more involving existing techniques, our algorithms are much simpler, i.e., using only random sampling, and achieving better performance ratios.

Cite as

Qilong Feng, Zhen Zhang, Ziyun Huang, Jinhui Xu, and Jianxin Wang. Improved Algorithms for Clustering with Outliers. In 30th International Symposium on Algorithms and Computation (ISAAC 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 149, pp. 61:1-61:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)


Copy BibTex To Clipboard

@InProceedings{feng_et_al:LIPIcs.ISAAC.2019.61,
  author =	{Feng, Qilong and Zhang, Zhen and Huang, Ziyun and Xu, Jinhui and Wang, Jianxin},
  title =	{{Improved Algorithms for Clustering with Outliers}},
  booktitle =	{30th International Symposium on Algorithms and Computation (ISAAC 2019)},
  pages =	{61:1--61:12},
  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.2019.61},
  URN =		{urn:nbn:de:0030-drops-115573},
  doi =		{10.4230/LIPIcs.ISAAC.2019.61},
  annote =	{Keywords: Clustering with Outliers, Approximation, Random Sampling}
}
Document
A Safety Argument Strategy for PCA Closed-Loop Systems: A Preliminary Proposal

Authors: Lu Feng, Andrew L. King, Sanjian Chen, Anaheed Ayoub, Junkil Park, Nicola Bezzo, Oleg Sokolsky, and Insup Lee

Published in: OASIcs, Volume 36, 5th Workshop on Medical Cyber-Physical Systems (2014)


Abstract
The emerging network-enabled medical devices impose new challenges for the safety assurance of medical cyber-physical systems (MCPS). In this paper, we present a case study of building a high-level safety argument for a patient-controlled analgesia (PCA) closed-loop system, with the purpose of exploring potential methodologies for assuring the safety of MCPS.

Cite as

Lu Feng, Andrew L. King, Sanjian Chen, Anaheed Ayoub, Junkil Park, Nicola Bezzo, Oleg Sokolsky, and Insup Lee. A Safety Argument Strategy for PCA Closed-Loop Systems: A Preliminary Proposal. In 5th Workshop on Medical Cyber-Physical Systems. Open Access Series in Informatics (OASIcs), Volume 36, pp. 94-99, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2014)


Copy BibTex To Clipboard

@InProceedings{feng_et_al:OASIcs.MCPS.2014.94,
  author =	{Feng, Lu and King, Andrew L. and Chen, Sanjian and Ayoub, Anaheed and Park, Junkil and Bezzo, Nicola and Sokolsky, Oleg and Lee, Insup},
  title =	{{A Safety Argument Strategy for PCA Closed-Loop Systems: A Preliminary Proposal}},
  booktitle =	{5th Workshop on Medical Cyber-Physical Systems},
  pages =	{94--99},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-66-8},
  ISSN =	{2190-6807},
  year =	{2014},
  volume =	{36},
  editor =	{Turau, Volker and Kwiatkowska, Marta and Mangharam, Rahul and Weyer, Christoph},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.MCPS.2014.94},
  URN =		{urn:nbn:de:0030-drops-45263},
  doi =		{10.4230/OASIcs.MCPS.2014.94},
  annote =	{Keywords: Medical Cyber-Physical Systems, Safety Argument, Assurance Cases, Patient-Controlled Analgesia Infusion Pump, Closed-Loop Systems}
}
  • Refine by Author
  • 2 Feng, Qilong
  • 2 Huang, Ziyun
  • 2 Wang, Jianxin
  • 2 Xu, Jinhui
  • 1 Ayoub, Anaheed
  • Show More...

  • Refine by Classification
  • 1 Theory of computation
  • 1 Theory of computation → Facility location and clustering
  • 1 Theory of computation → Pattern matching

  • Refine by Keyword
  • 1 Alignment
  • 1 Approximate algorithm
  • 1 Approximation
  • 1 Assurance Cases
  • 1 Bipartite matching
  • Show More...

  • Refine by Type
  • 3 document

  • Refine by Publication Year
  • 2 2019
  • 1 2014

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