{"title":"Space-filling designs on Riemannian manifolds","authors":"Mingyao Ai , Yunfan Yang , Xiangshun Kong","doi":"10.1016/j.jco.2024.101899","DOIUrl":"10.1016/j.jco.2024.101899","url":null,"abstract":"<div><div>This paper proposes a new approach to generating space-filling designs over Riemannian manifolds by using a Hilbert curve. Different from ordinary Euclidean spaces, a novel transformation is constructed to link the uniform distribution over a Riemannian manifold and that over its parameter space. Using this transformation, the uniformity of the design points in the sense of Riemannian volume measure can be guaranteed by the intrinsic measure preserving property of the Hilbert curve. It is proved that these generated designs are not only asymptotically optimal under minimax and maximin distance criteria, but also perform well in minimizing the Wasserstein distance from the target distribution and controlling the estimation error in numerical integration. Furthermore, an efficient algorithm is developed for numerical generation of these space-filling designs. The advantages of the new approach are verified through numerical simulations.</div></div>","PeriodicalId":50227,"journal":{"name":"Journal of Complexity","volume":"86 ","pages":"Article 101899"},"PeriodicalIF":1.8,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142319731","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"On the number of solutions to a random instance of the permuted kernel problem","authors":"Carlo Sanna","doi":"10.1016/j.jco.2024.101898","DOIUrl":"10.1016/j.jco.2024.101898","url":null,"abstract":"<div><div>The <em>Permuted Kernel Problem</em> (PKP) is a problem in linear algebra that was first introduced by Shamir in 1989. Roughly speaking, given an <span><math><mi>ℓ</mi><mo>×</mo><mi>m</mi></math></span> matrix <strong><em>A</em></strong> and an <span><math><mi>m</mi><mo>×</mo><mn>1</mn></math></span> vector <strong><em>b</em></strong> over a finite field of <em>q</em> elements <span><math><msub><mrow><mi>F</mi></mrow><mrow><mi>q</mi></mrow></msub></math></span>, the PKP asks to find an <span><math><mi>m</mi><mo>×</mo><mi>m</mi></math></span> permutation matrix <strong><em>π</em></strong> such that <span><math><mi>π</mi><mi>b</mi></math></span> belongs to the kernel of <strong><em>A</em></strong>. In recent years, several post-quantum digital signature schemes whose security can be provably reduced to the hardness of solving random instances of the PKP have been proposed. In this regard, it is important to know the expected number of solutions to a random instance of the PKP in terms of the parameters <span><math><mi>q</mi><mo>,</mo><mi>ℓ</mi><mo>,</mo><mi>m</mi></math></span>. Previous works have heuristically estimated the expected number of solutions to be <span><math><mi>m</mi><mo>!</mo><mo>/</mo><msup><mrow><mi>q</mi></mrow><mrow><mi>ℓ</mi></mrow></msup></math></span>.</div><div>We provide, and rigorously prove, exact formulas for the expected number of solutions to a random instance of the PKP and the related <em>Inhomogeneous Permuted Kernel Problem</em> (IPKP), considering two natural ways of generating random instances.</div></div>","PeriodicalId":50227,"journal":{"name":"Journal of Complexity","volume":"86 ","pages":"Article 101898"},"PeriodicalIF":1.8,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0885064X2400075X/pdfft?md5=939873f4b51043507214927d47f2bb37&pid=1-s2.0-S0885064X2400075X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142314359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Convergence analysis of iteratively regularized Landweber iteration with uniformly convex constraints in Banach spaces","authors":"Gaurav Mittal , Harshit Bajpai , Ankik Kumar Giri","doi":"10.1016/j.jco.2024.101897","DOIUrl":"10.1016/j.jco.2024.101897","url":null,"abstract":"<div><p>In Banach spaces, the convergence analysis of iteratively regularized Landweber iteration (IRLI) is recently studied via conditional stability estimates. But the formulation of IRLI does not include general non-smooth convex penalty functionals, which is essential to capture special characteristics of the sought solution. In this paper, we formulate a generalized form of IRLI so that its formulation includes general non-smooth uniformly convex penalty functionals. We study the convergence analysis and derive the convergence rates of the generalized method solely via conditional stability estimates in Banach spaces for both the perturbed and unperturbed data. We also discuss few examples of inverse problems on which our method is applicable.</p></div>","PeriodicalId":50227,"journal":{"name":"Journal of Complexity","volume":"86 ","pages":"Article 101897"},"PeriodicalIF":1.8,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0885064X24000748/pdfft?md5=5ae8eeac0a143f493ee150c18db69cf1&pid=1-s2.0-S0885064X24000748-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142240454","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"High-efficiency parametric iterative schemes for solving nonlinear equations with and without memory","authors":"Raziyeh Erfanifar, Masoud Hajarian","doi":"10.1016/j.jco.2024.101896","DOIUrl":"10.1016/j.jco.2024.101896","url":null,"abstract":"<div><p>Many practical problems, such as the Malthusian population growth model, eigenvalue computations for matrices, and solving the Van der Waals' ideal gas equation, inherently involve nonlinearities. This paper initially introduces a two-parameter iterative scheme with a convergence order of two. Building on this, a three-parameter scheme with a convergence order of four is proposed. Then we extend these schemes into higher-order schemes with memory using Newton's interpolation, achieving an upper bound for the efficiency index of <span><math><msup><mrow><mn>7.88748</mn></mrow><mrow><mfrac><mrow><mn>1</mn></mrow><mrow><mn>3</mn></mrow></mfrac></mrow></msup><mo>≈</mo><mn>1.99057</mn></math></span>. Finally, we validate the new schemes by solving various numerical and practical examples, demonstrating their superior efficiency in terms of computational cost, CPU time, and accuracy compared to existing methods.</p></div>","PeriodicalId":50227,"journal":{"name":"Journal of Complexity","volume":"86 ","pages":"Article 101896"},"PeriodicalIF":1.8,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0885064X24000736/pdfft?md5=6dc221bf6c1e2ffc085c2b830768b4e4&pid=1-s2.0-S0885064X24000736-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142240453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"On the approximation of vector-valued functions by volume sampling","authors":"Daniel Kressner , Tingting Ni , André Uschmajew","doi":"10.1016/j.jco.2024.101887","DOIUrl":"10.1016/j.jco.2024.101887","url":null,"abstract":"<div><p>Given a Hilbert space <span><math><mi>H</mi></math></span> and a finite measure space Ω, the approximation of a vector-valued function <span><math><mi>f</mi><mo>:</mo><mi>Ω</mi><mo>→</mo><mi>H</mi></math></span> by a <em>k</em>-dimensional subspace <span><math><mi>U</mi><mo>⊂</mo><mi>H</mi></math></span> plays an important role in dimension reduction techniques, such as reduced basis methods for solving parameter-dependent partial differential equations. For functions in the Lebesgue–Bochner space <span><math><msup><mrow><mi>L</mi></mrow><mrow><mn>2</mn></mrow></msup><mo>(</mo><mi>Ω</mi><mo>;</mo><mi>H</mi><mo>)</mo></math></span>, the best possible subspace approximation error <span><math><msubsup><mrow><mi>d</mi></mrow><mrow><mi>k</mi></mrow><mrow><mo>(</mo><mn>2</mn><mo>)</mo></mrow></msubsup></math></span> is characterized by the singular values of <em>f</em>. However, for practical reasons, <span><math><mi>U</mi></math></span> is often restricted to be spanned by point samples of <em>f</em>. We show that this restriction only has a mild impact on the attainable error; there always exist <em>k</em> samples such that the resulting error is not larger than <span><math><msqrt><mrow><mi>k</mi><mo>+</mo><mn>1</mn></mrow></msqrt><mo>⋅</mo><msubsup><mrow><mi>d</mi></mrow><mrow><mi>k</mi></mrow><mrow><mo>(</mo><mn>2</mn><mo>)</mo></mrow></msubsup></math></span>. Our work extends existing results by Binev et al. (2011) <span><span>[3]</span></span> on approximation in supremum norm and by Deshpande et al. (2006) <span><span>[8]</span></span> on column subset selection for matrices.</p></div>","PeriodicalId":50227,"journal":{"name":"Journal of Complexity","volume":"86 ","pages":"Article 101887"},"PeriodicalIF":1.8,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0885064X24000645/pdfft?md5=810287a810b23405b1bc8161d82ba70e&pid=1-s2.0-S0885064X24000645-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141935983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"High probability bounds on AdaGrad for constrained weakly convex optimization","authors":"Yusu Hong , Junhong Lin","doi":"10.1016/j.jco.2024.101889","DOIUrl":"10.1016/j.jco.2024.101889","url":null,"abstract":"<div><p>In this paper, we study the high probability convergence of AdaGrad-Norm for constrained, non-smooth, weakly convex optimization with bounded noise and sub-Gaussian noise cases. We also investigate a more general accelerated gradient descent (AGD) template (Ghadimi and Lan, 2016) encompassing the AdaGrad-Norm, the Nesterov's accelerated gradient descent, and the RSAG (Ghadimi and Lan, 2016) with different parameter choices. We provide a high probability convergence rate <span><math><mover><mrow><mi>O</mi></mrow><mrow><mo>˜</mo></mrow></mover><mo>(</mo><mn>1</mn><mo>/</mo><msqrt><mrow><mi>T</mi></mrow></msqrt><mo>)</mo></math></span> without knowing the information of the weak convexity parameter and the gradient bound to tune the step-sizes.</p></div>","PeriodicalId":50227,"journal":{"name":"Journal of Complexity","volume":"86 ","pages":"Article 101889"},"PeriodicalIF":1.8,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0885064X24000669/pdfft?md5=7c5c4999e38fd8c865761fe3213f35cf&pid=1-s2.0-S0885064X24000669-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141935984","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"No existence of a linear algorithm for the one-dimensional Fourier phase retrieval","authors":"Meng Huang , Zhiqiang Xu","doi":"10.1016/j.jco.2024.101886","DOIUrl":"10.1016/j.jco.2024.101886","url":null,"abstract":"<div><p>Fourier phase retrieval, which aims to reconstruct a signal from its Fourier magnitude, is of fundamental importance in fields of engineering and science. In this paper, we provide a theoretical understanding of algorithms for the one-dimensional Fourier phase retrieval problem. Specifically, we demonstrate that if an algorithm exists which can reconstruct an arbitrary signal <span><math><mi>x</mi><mo>∈</mo><msup><mrow><mi>C</mi></mrow><mrow><mi>N</mi></mrow></msup></math></span> in <span><math><mtext>Poly</mtext><mo>(</mo><mi>N</mi><mo>)</mo><mi>log</mi><mo></mo><mo>(</mo><mn>1</mn><mo>/</mo><mi>ϵ</mi><mo>)</mo></math></span> time to reach <em>ϵ</em>-precision from its magnitude of discrete Fourier transform and its initial value <span><math><mi>x</mi><mo>(</mo><mn>0</mn><mo>)</mo></math></span>, then <span><math><mi>P</mi><mo>=</mo><mrow><mi>NP</mi></mrow></math></span>. This partially elucidates the phenomenon that, despite the fact that almost all signals are uniquely determined by their Fourier magnitude and the absolute value of their initial value <span><math><mo>|</mo><mi>x</mi><mo>(</mo><mn>0</mn><mo>)</mo><mo>|</mo></math></span>, no algorithm with theoretical guarantees has been proposed in the last few decades. Our proofs employ the result in computational complexity theory that the Product Partition problem is NP-complete in the strong sense.</p></div>","PeriodicalId":50227,"journal":{"name":"Journal of Complexity","volume":"86 ","pages":"Article 101886"},"PeriodicalIF":1.8,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0885064X24000633/pdfft?md5=306cc05c455de6efb9f908455c6f3128&pid=1-s2.0-S0885064X24000633-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141637397","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Interpolation by decomposable univariate polynomials","authors":"Joachim von zur Gathen , Guillermo Matera","doi":"10.1016/j.jco.2024.101885","DOIUrl":"10.1016/j.jco.2024.101885","url":null,"abstract":"<div><p>The usual univariate interpolation problem of finding a monic polynomial <em>f</em> of degree <em>n</em> that interpolates <em>n</em> given values is well understood. This paper studies a variant where <em>f</em> is required to be composite, say, a composition of two polynomials of degrees <em>d</em> and <em>e</em>, respectively, with <span><math><mi>d</mi><mi>e</mi><mo>=</mo><mi>n</mi></math></span>, and with <span><math><mi>d</mi><mo>+</mo><mi>e</mi><mo>−</mo><mn>1</mn></math></span> given values. Some special cases are easy to solve, and for the general case, we construct a homotopy between it and a special case. We compute a <em>geometric solution</em> of the algebraic curve presenting this homotopy, and this also provides an answer to the interpolation task. The computing time is polynomial in the geometric data, like the degree, of this curve. A consequence is that for almost all inputs, a decomposable interpolation polynomial exists.</p></div>","PeriodicalId":50227,"journal":{"name":"Journal of Complexity","volume":"85 ","pages":"Article 101885"},"PeriodicalIF":1.8,"publicationDate":"2024-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141501488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Sharp lower bounds on the manifold widths of Sobolev and Besov spaces","authors":"Jonathan W. Siegel","doi":"10.1016/j.jco.2024.101884","DOIUrl":"https://doi.org/10.1016/j.jco.2024.101884","url":null,"abstract":"<div><p>We study the manifold <em>n</em>-widths of Sobolev and Besov spaces with error measured in the <span><math><msub><mrow><mi>L</mi></mrow><mrow><mi>p</mi></mrow></msub></math></span>-norm. The manifold widths measure how efficiently these spaces can be approximated by continuous non-linear parametric methods. Existing upper and lower bounds only match when the smoothness index <em>q</em> satisfies <span><math><mi>q</mi><mo>≤</mo><mi>p</mi></math></span> or <span><math><mn>1</mn><mo>≤</mo><mi>p</mi><mo>≤</mo><mn>2</mn></math></span>. We close this gap, obtaining sharp bounds for all <span><math><mn>1</mn><mo>≤</mo><mi>p</mi><mo>,</mo><mi>q</mi><mo>≤</mo><mo>∞</mo></math></span> for which a compact embedding holds. In the process, we determine the exact value of the manifold widths of finite dimensional <span><math><msubsup><mrow><mi>ℓ</mi></mrow><mrow><mi>q</mi></mrow><mrow><mi>M</mi></mrow></msubsup></math></span>-balls in the <span><math><msub><mrow><mi>ℓ</mi></mrow><mrow><mi>p</mi></mrow></msub></math></span>-norm when <span><math><mi>p</mi><mo>≤</mo><mi>q</mi></math></span>. Although this result is not new, we provide a new proof and apply it to lower bounding the manifold widths of Sobolev and Besov spaces. Our results show that the Bernstein widths, which are typically used to lower bound the manifold widths, decay asymptotically faster than the manifold widths in many cases.</p></div>","PeriodicalId":50227,"journal":{"name":"Journal of Complexity","volume":"85 ","pages":"Article 101884"},"PeriodicalIF":1.8,"publicationDate":"2024-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141485089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Minimal dispersion on the cube and the torus","authors":"A. Arman , A.E. Litvak","doi":"10.1016/j.jco.2024.101883","DOIUrl":"10.1016/j.jco.2024.101883","url":null,"abstract":"<div><p>We improve some upper bounds for minimal dispersion on the cube and torus. Our new ingredient is an improvement of a probabilistic lemma used to obtain upper bounds for dispersion in several previous works. Our new lemma combines a random and non-random choice of points in the cube. This leads to better upper bounds for the minimal dispersion.</p></div>","PeriodicalId":50227,"journal":{"name":"Journal of Complexity","volume":"85 ","pages":"Article 101883"},"PeriodicalIF":1.7,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0885064X24000608/pdfft?md5=8545345a37c7c8d8bd458b82060fc777&pid=1-s2.0-S0885064X24000608-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141408812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}