3 Search Results for "Wu, Yi"


Document
Track A: Algorithms, Complexity and Games
Quantum Algorithms and Lower Bounds for Linear Regression with Norm Constraints

Authors: Yanlin Chen and Ronald de Wolf

Published in: LIPIcs, Volume 261, 50th International Colloquium on Automata, Languages, and Programming (ICALP 2023)


Abstract
Lasso and Ridge are important minimization problems in machine learning and statistics. They are versions of linear regression with squared loss where the vector θ ∈ ℝ^d of coefficients is constrained in either 𝓁₁-norm (for Lasso) or in 𝓁₂-norm (for Ridge). We study the complexity of quantum algorithms for finding ε-minimizers for these minimization problems. We show that for Lasso we can get a quadratic quantum speedup in terms of d by speeding up the cost-per-iteration of the Frank-Wolfe algorithm, while for Ridge the best quantum algorithms are linear in d, as are the best classical algorithms. As a byproduct of our quantum lower bound for Lasso, we also prove the first classical lower bound for Lasso that is tight up to polylog-factors.

Cite as

Yanlin Chen and Ronald de Wolf. Quantum Algorithms and Lower Bounds for Linear Regression with Norm Constraints. In 50th International Colloquium on Automata, Languages, and Programming (ICALP 2023). Leibniz International Proceedings in Informatics (LIPIcs), Volume 261, pp. 38:1-38:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)


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@InProceedings{chen_et_al:LIPIcs.ICALP.2023.38,
  author =	{Chen, Yanlin and de Wolf, Ronald},
  title =	{{Quantum Algorithms and Lower Bounds for Linear Regression with Norm Constraints}},
  booktitle =	{50th International Colloquium on Automata, Languages, and Programming (ICALP 2023)},
  pages =	{38:1--38:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-278-5},
  ISSN =	{1868-8969},
  year =	{2023},
  volume =	{261},
  editor =	{Etessami, Kousha and Feige, Uriel and Puppis, Gabriele},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ICALP.2023.38},
  URN =		{urn:nbn:de:0030-drops-180907},
  doi =		{10.4230/LIPIcs.ICALP.2023.38},
  annote =	{Keywords: Quantum algorithms, Regularized linear regression, Lasso, Ridge, Lower bounds}
}
Document
The Most Parsimonious Reconciliation Problem in the Presence of Incomplete Lineage Sorting and Hybridization Is NP-Hard

Authors: Matthew LeMay, Yi-Chieh Wu, and Ran Libeskind-Hadas

Published in: LIPIcs, Volume 201, 21st International Workshop on Algorithms in Bioinformatics (WABI 2021)


Abstract
The maximum parsimony phylogenetic reconciliation problem seeks to explain incongruity between a gene phylogeny and a species phylogeny with respect to a set of evolutionary events. While the reconciliation problem is well-studied for species and gene trees subject to events such as duplication, transfer, loss, and deep coalescence, recent work has examined species phylogenies that incorporate hybridization and are thus represented by networks rather than trees. In this paper, we show that the problem of computing a maximum parsimony reconciliation for a gene tree and species network is NP-hard even when only considering deep coalescence. This result suggests that future work on maximum parsimony reconciliation for species networks should explore approximation algorithms and heuristics.

Cite as

Matthew LeMay, Yi-Chieh Wu, and Ran Libeskind-Hadas. The Most Parsimonious Reconciliation Problem in the Presence of Incomplete Lineage Sorting and Hybridization Is NP-Hard. In 21st International Workshop on Algorithms in Bioinformatics (WABI 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 201, pp. 1:1-1:10, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)


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@InProceedings{lemay_et_al:LIPIcs.WABI.2021.1,
  author =	{LeMay, Matthew and Wu, Yi-Chieh and Libeskind-Hadas, Ran},
  title =	{{The Most Parsimonious Reconciliation Problem in the Presence of Incomplete Lineage Sorting and Hybridization Is NP-Hard}},
  booktitle =	{21st International Workshop on Algorithms in Bioinformatics (WABI 2021)},
  pages =	{1:1--1:10},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-200-6},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{201},
  editor =	{Carbone, Alessandra and El-Kebir, Mohammed},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.WABI.2021.1},
  URN =		{urn:nbn:de:0030-drops-143546},
  doi =		{10.4230/LIPIcs.WABI.2021.1},
  annote =	{Keywords: phylogenetics, reconciliation, deep coalescence, hybridization, NP-hardness}
}
Document
Computational Complexity of Certifying Restricted Isometry Property

Authors: Abhiram Natarajan and Yi Wu

Published in: LIPIcs, Volume 28, Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2014)


Abstract
Given a matrix A with n rows, a number k < n, and 0 < delta < 1, A is (k,delta)-RIP (Restricted Isometry Property) if, for any vector x in R^n, with at most k non-zero co-ordinates, (1-delta)|x|^2 <= |Ax|^2 <= (1+delta)|Ax|^2. In many applications, such as compressed sensing and sparse recovery, it is desirable to construct RIP matrices with a large k and a small delta;. Given the efficacy of random constructions in generating useful RIP matrices, the problem of certifying the RIP parameters of a matrix has become important. In this paper, we prove that it is hard to approximate the RIP parameters of a matrix assuming the Small-Set-Expansion-Hypothesis. Specifically, we prove that for any arbitrarily large constant C>0 and any arbitrarily small constant 0<delta<1, there exists some k such that given a matrix M, it is SSE-Hard to distinguish the following two cases: i) (Highly RIP) M is (k,delta)-RIP; ii) (Far away from RIP) M is not (k/C,1-delta)-RIP. Most of the previous results on the topic of hardness of RIP certification only hold for certification when delta=o(1). In practice, it is of interest to understand the complexity of certifying a matrix with delta being close to sqrt(2) - 1, as it suffices for many real applications to have matrices with delta=sqrt(2)-1. Our hardness result holds for any constant delta. Specifically, our result proves that even if delta is indeed very small, i.e. the matrix is in fact strongly RIP, certifying that the matrix exhibits weak RIP itself is SSE-Hard. In order to prove the hardness result, we prove a variant of the Cheeger's Inequality for sparse vectors.

Cite as

Abhiram Natarajan and Yi Wu. Computational Complexity of Certifying Restricted Isometry Property. In Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2014). Leibniz International Proceedings in Informatics (LIPIcs), Volume 28, pp. 371-380, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2014)


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@InProceedings{natarajan_et_al:LIPIcs.APPROX-RANDOM.2014.371,
  author =	{Natarajan, Abhiram and Wu, Yi},
  title =	{{Computational Complexity of Certifying Restricted Isometry Property}},
  booktitle =	{Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2014)},
  pages =	{371--380},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-939897-74-3},
  ISSN =	{1868-8969},
  year =	{2014},
  volume =	{28},
  editor =	{Jansen, Klaus and Rolim, Jos\'{e} and Devanur, Nikhil R. and Moore, Cristopher},
  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.2014.371},
  URN =		{urn:nbn:de:0030-drops-47092},
  doi =		{10.4230/LIPIcs.APPROX-RANDOM.2014.371},
  annote =	{Keywords: Restricted Isometry Property, RIP, RIP Certification, Sparse Cheeger Inequality, SSE Hard}
}
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