4 Search Results for "Zhang, Qin"

Document
DOI: 10.4230/LIPIcs.SWAT.2022.25
An Almost Optimal Algorithm for Unbounded Search with Noisy Information

Authors: Junhao Gan, Anthony Wirth, and Xin Zhang

Published in: LIPIcs, Volume 227, 18th Scandinavian Symposium and Workshops on Algorithm Theory (SWAT 2022)

Abstract
Given a sequence of integers, 𝒮 = s₁, s₂,… in ascending order, called the search domain, and an integer t, called the target, the predecessor problem asks for the target index N such that s_N is the largest integer in 𝒮 satisfying s_N ≤ t. We consider solving the predecessor problem with the least number of queries to a binary comparison oracle. For each query index i, the oracle returns whether s_i ≤ t or s_i > t. In particular, we study the predecessor problem under the UnboundedNoisy setting, where (i) the search domain 𝒮 is unbounded, i.e., n = |𝒮| is unknown or infinite, and (ii) the binary comparison oracle is noisy. We denote the former setting by Unbounded and the latter by Noisy. In Noisy, the oracle, for each query, independently returns a wrong answer with a fixed constant probability 0 < p < 1/2. In particular, even for two queries on the same index i, the answers from the oracle may be different. Furthermore, with a noisy oracle, the goal is to correctly return the target index with probability at least 1- Q, where 0 < Q < 1/2 is the failure probability. Our first result is an algorithm, called NoS, for Noisy that improves the previous result by Ben-Or and Hassidim [FOCS 2008] from an expected query complexity bound to a worst-case bound. We also achieve an expected query complexity bound, whose leading term has an optimal constant factor, matching the lower bound of Ben-Or and Hassidim. Building on NoS, we propose our NoSU algorithm, which correctly solves the predecessor problem in the UnboundedNoisy setting. We prove that the query complexity of NoSU is ∑_{i = 1}^k (log^{(i)} N) /(1-H(p))+ o(log N) when log Q^{-1} ∈ o(log N), where N is the target index, k = log^* N, the iterated logarithm, and H(p) is the entropy function. This improves the previous bound of O(log (N/Q) / (1-H(p))) by reducing the coefficient of the leading term from a large constant to 1. Moreover, we show that this upper bound can be further improved to (1 - Q) ∑_{i = 1}^k (log^{(i)} N) /(1-H(p))+ o(log N) in expectation, with the constant in the leading term reduced to 1 - Q. Finally, we show that an information-theoretic lower bound on the expected query cost of the predecessor problem in UnboundedNoisy is at least (1 - Q)(∑_{i = 1}^k log^{(i)} N - 2k)/(1-H(p)) - 10. This implies the constant factor in the leading term of our expected upper bound is indeed optimal.
Cite as

Junhao Gan, Anthony Wirth, and Xin Zhang. An Almost Optimal Algorithm for Unbounded Search with Noisy Information. In 18th Scandinavian Symposium and Workshops on Algorithm Theory (SWAT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 227, pp. 25:1-25:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)

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@InProceedings{gan_et_al:LIPIcs.SWAT.2022.25,
  author =	{Gan, Junhao and Wirth, Anthony and Zhang, Xin},
  title =	{{An Almost Optimal Algorithm for Unbounded Search with Noisy Information}},
  booktitle =	{18th Scandinavian Symposium and Workshops on Algorithm Theory (SWAT 2022)},
  pages =	{25:1--25:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-236-5},
  ISSN =	{1868-8969},
  year =	{2022},
  volume =	{227},
  editor =	{Czumaj, Artur and Xin, Qin},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.SWAT.2022.25},
  URN =		{urn:nbn:de:0030-drops-161854},
  doi =		{10.4230/LIPIcs.SWAT.2022.25},
  annote =	{Keywords: Fault-tolerant search, noisy binary search, query complexity}
}
Document
DOI: 10.4230/LIPIcs.STACS.2021.45
An Improved Sketching Algorithm for Edit Distance

Authors: Ce Jin, Jelani Nelson, and Kewen Wu

Published in: LIPIcs, Volume 187, 38th International Symposium on Theoretical Aspects of Computer Science (STACS 2021)

Abstract
We provide improved upper bounds for the simultaneous sketching complexity of edit distance. Consider two parties, Alice with input x ∈ Σⁿ and Bob with input y ∈ Σⁿ, that share public randomness and are given a promise that the edit distance ed(x,y) between their two strings is at most some given value k. Alice must send a message sx and Bob must send sy to a third party Charlie, who does not know the inputs but shares the same public randomness and also knows k. Charlie must output ed(x,y) precisely as well as a sequence of ed(x,y) edits required to transform x into y. The goal is to minimize the lengths |sx|, |sy| of the messages sent. The protocol of Belazzougui and Zhang (FOCS 2016), building upon the random walk method of Chakraborty, Goldenberg, and Koucký (STOC 2016), achieves a maximum message length of Õ(k⁸) bits, where Õ(⋅) hides poly(log n) factors. In this work we build upon Belazzougui and Zhang’s protocol and provide an improved analysis demonstrating that a slight modification of their construction achieves a bound of Õ(k³).
Cite as

Ce Jin, Jelani Nelson, and Kewen Wu. An Improved Sketching Algorithm for Edit Distance. In 38th International Symposium on Theoretical Aspects of Computer Science (STACS 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 187, pp. 45:1-45:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{jin_et_al:LIPIcs.STACS.2021.45,
  author =	{Jin, Ce and Nelson, Jelani and Wu, Kewen},
  title =	{{An Improved Sketching Algorithm for Edit Distance}},
  booktitle =	{38th International Symposium on Theoretical Aspects of Computer Science (STACS 2021)},
  pages =	{45:1--45:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-180-1},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{187},
  editor =	{Bl\"{a}ser, Markus and Monmege, Benjamin},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.STACS.2021.45},
  URN =		{urn:nbn:de:0030-drops-136905},
  doi =		{10.4230/LIPIcs.STACS.2021.45},
  annote =	{Keywords: edit distance, sketching}
}
Document
RANDOM
DOI: 10.4230/LIPIcs.APPROX-RANDOM.2019.69
Approximate F_2-Sketching of Valuation Functions

Authors: Grigory Yaroslavtsev and Samson Zhou

Published in: LIPIcs, Volume 145, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2019)

Abstract
We study the problem of constructing a linear sketch of minimum dimension that allows approximation of a given real-valued function f : F_2^n - > R with small expected squared error. We develop a general theory of linear sketching for such functions through which we analyze their dimension for most commonly studied types of valuation functions: additive, budget-additive, coverage, alpha-Lipschitz submodular and matroid rank functions. This gives a characterization of how many bits of information have to be stored about the input x so that one can compute f under additive updates to its coordinates. Our results are tight in most cases and we also give extensions to the distributional version of the problem where the input x in F_2^n is generated uniformly at random. Using known connections with dynamic streaming algorithms, both upper and lower bounds on dimension obtained in our work extend to the space complexity of algorithms evaluating f(x) under long sequences of additive updates to the input x presented as a stream. Similar results hold for simultaneous communication in a distributed setting.
Cite as

Grigory Yaroslavtsev and Samson Zhou. Approximate F_2-Sketching of Valuation Functions. In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 145, pp. 69:1-69:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{yaroslavtsev_et_al:LIPIcs.APPROX-RANDOM.2019.69,
  author =	{Yaroslavtsev, Grigory and Zhou, Samson},
  title =	{{Approximate F\underline2-Sketching of Valuation Functions}},
  booktitle =	{Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2019)},
  pages =	{69:1--69:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-125-2},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{145},
  editor =	{Achlioptas, Dimitris and V\'{e}gh, L\'{a}szl\'{o} A.},
  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.2019.69},
  URN =		{urn:nbn:de:0030-drops-112848},
  doi =		{10.4230/LIPIcs.APPROX-RANDOM.2019.69},
  annote =	{Keywords: Sublinear algorithms, linear sketches, approximation algorithms}
}
Document
DOI: 10.4230/LIPIcs.STACS.2015.460
Communication Complexity of Approximate Matching in Distributed Graphs

Authors: Zengfeng Huang, Bozidar Radunovic, Milan Vojnovic, and Qin Zhang

Published in: LIPIcs, Volume 30, 32nd International Symposium on Theoretical Aspects of Computer Science (STACS 2015)

Abstract
In this paper we consider the communication complexity of approximation algorithms for maximum matching in a graph in the message-passing model of distributed computation. The input graph consists of n vertices and edges partitioned over a set of k sites. The output is an \alpha-approximate maximum matching in the input graph which has to be reported by one of the sites. We show a lower bound on the communication complexity of \Omega(\alpha^2 k n) and show that it is tight up to poly-logarithmic factors. This lower bound also applies to other combinatorial problems on graphs in the message-passing computation model, including max-flow and graph sparsification.
Cite as

Zengfeng Huang, Bozidar Radunovic, Milan Vojnovic, and Qin Zhang. Communication Complexity of Approximate Matching in Distributed Graphs. In 32nd International Symposium on Theoretical Aspects of Computer Science (STACS 2015). Leibniz International Proceedings in Informatics (LIPIcs), Volume 30, pp. 460-473, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2015)

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@InProceedings{huang_et_al:LIPIcs.STACS.2015.460,
  author =	{Huang, Zengfeng and Radunovic, Bozidar and Vojnovic, Milan and Zhang, Qin},
  title =	{{Communication Complexity of Approximate Matching in Distributed Graphs}},
  booktitle =	{32nd International Symposium on Theoretical Aspects of Computer Science (STACS 2015)},
  pages =	{460--473},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-939897-78-1},
  ISSN =	{1868-8969},
  year =	{2015},
  volume =	{30},
  editor =	{Mayr, Ernst W. and Ollinger, Nicolas},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.STACS.2015.460},
  URN =		{urn:nbn:de:0030-drops-49348},
  doi =		{10.4230/LIPIcs.STACS.2015.460},
  annote =	{Keywords: approximate maximum matching, distributed computation, communication complexity}
}
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