{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T20:37:45Z","timestamp":1776803865393,"version":"3.51.2"},"reference-count":23,"publisher":"American Mathematical Society (AMS)","issue":"313","license":[{"start":{"date-parts":[[2018,12,14]],"date-time":"2018-12-14T00:00:00Z","timestamp":1544745600000},"content-version":"am","delay-in-days":365,"URL":"https:\/\/www.ams.org\/publications\/copyright-and-permissions"}],"funder":[{"DOI":"10.13039\/501100001659","name":"Deutsche Forschungsgemeinschaft","doi-asserted-by":"publisher","award":["KR 4512\/1-1"],"award-info":[{"award-number":["KR 4512\/1-1"]}],"id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Math. Comp."],"abstract":"<p>\n                    <inline-formula content-type=\"math\/mathml\">\n                      <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" alttext=\"script l 1\">\n                        <mml:semantics>\n                          <mml:msub>\n                            <mml:mi>\n                              \u2113\n                              \n                            <\/mml:mi>\n                            <mml:mn>1<\/mml:mn>\n                          <\/mml:msub>\n                          <mml:annotation encoding=\"application\/x-tex\">\\ell _1<\/mml:annotation>\n                        <\/mml:semantics>\n                      <\/mml:math>\n                    <\/inline-formula>\n                    -regularized linear inverse problems frequently arise in signal processing, image analysis, and statistics. The correct choice of the regularization parameter\n                    <inline-formula content-type=\"math\/mathml\">\n                      <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" alttext=\"t element-of double-struck upper R Subscript greater-than-or-equal-to 0\">\n                        <mml:semantics>\n                          <mml:mrow>\n                            <mml:mi>t<\/mml:mi>\n                            <mml:mo>\n                              \u2208\n                              \n                            <\/mml:mo>\n                            <mml:msub>\n                              <mml:mrow class=\"MJX-TeXAtom-ORD\">\n                                <mml:mi mathvariant=\"double-struck\">R<\/mml:mi>\n                              <\/mml:mrow>\n                              <mml:mrow class=\"MJX-TeXAtom-ORD\">\n                                <mml:mo>\n                                  \u2265\n                                  \n                                <\/mml:mo>\n                                <mml:mn>0<\/mml:mn>\n                              <\/mml:mrow>\n                            <\/mml:msub>\n                          <\/mml:mrow>\n                          <mml:annotation encoding=\"application\/x-tex\">t \\in \\mathbb {R}_{\\geq 0}<\/mml:annotation>\n                        <\/mml:semantics>\n                      <\/mml:math>\n                    <\/inline-formula>\n                    is a delicate issue. Instead of solving the variational problem for a fixed parameter, the idea of the homotopy method is to compute a complete solution path\n                    <inline-formula content-type=\"math\/mathml\">\n                      <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" alttext=\"u left-parenthesis t right-parenthesis\">\n                        <mml:semantics>\n                          <mml:mrow>\n                            <mml:mi>u<\/mml:mi>\n                            <mml:mo stretchy=\"false\">(<\/mml:mo>\n                            <mml:mi>t<\/mml:mi>\n                            <mml:mo stretchy=\"false\">)<\/mml:mo>\n                          <\/mml:mrow>\n                          <mml:annotation encoding=\"application\/x-tex\">u(t)<\/mml:annotation>\n                        <\/mml:semantics>\n                      <\/mml:math>\n                    <\/inline-formula>\n                    as a function of\n                    <inline-formula content-type=\"math\/mathml\">\n                      <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" alttext=\"t\">\n                        <mml:semantics>\n                          <mml:mi>t<\/mml:mi>\n                          <mml:annotation encoding=\"application\/x-tex\">t<\/mml:annotation>\n                        <\/mml:semantics>\n                      <\/mml:math>\n                    <\/inline-formula>\n                    . In their celebrated paper\n                    <italic>A new approach to variable selection in least squares problems<\/italic>\n                    [IMA J. Numer. Anal.\n                    <bold>20<\/bold>\n                    (2000), no.\u00a03, 389\u2013403], Osborne, Presnell, and Turlach showed that the computational cost of this approach is often comparable to the cost of solving the corresponding least squares problem. Their analysis relies on the one-at-a-time condition, which requires that different indices enter or leave the support of the solution at distinct regularization parameters. In this paper, we introduce a generalized homotopy algorithm based on a nonnegative least squares problem, which does not require such a condition, and prove its termination after finitely many steps. At every point of the path, we give a full characterization of all possible directions. To illustrate our results, we discuss examples in which the standard homotopy method either fails or becomes infeasible. To the best of our knowledge, our algorithm is the first to provably compute a full piecewise linear and continuous solution path for an arbitrary combination of a measurement matrix and a data vector.\n                  <\/p>","DOI":"10.1090\/mcom\/3287","type":"journal-article","created":{"date-parts":[[2017,5,24]],"date-time":"2017-05-24T09:49:33Z","timestamp":1495619373000},"page":"2343-2364","source":"Crossref","is-referenced-by-count":5,"title":["The homotopy method revisited: Computing solution paths of \u2113\u2081-regularized problems"],"prefix":"10.1090","volume":"87","author":[{"given":"Bjoern","family":"Bringmann","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daniel","family":"Cremers","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Felix","family":"Krahmer","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Michael","family":"Moeller","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"14","published-online":{"date-parts":[[2017,12,14]]},"reference":[{"key":"1","doi-asserted-by":"crossref","unstructured":"Arjan Berkelaar, Kees Roos, and Tamas Terlaky, The optimal set and optimal partition approach to linear and quadratic programming, Springer, 1996, pp. 159\u2013202.","DOI":"10.1007\/978-1-4615-6103-3_6"},{"key":"2","isbn-type":"print","first-page":"57","article-title":"An algorithm for the solution of the parametric quadratic programming problem","author":"Best, Michael J.","year":"1996","ISBN":"https:\/\/id.crossref.org\/isbn\/379080939X"},{"issue":"3","key":"3","doi-asserted-by":"publisher","first-page":"1374","DOI":"10.1137\/15M1054687","article-title":"Spectral decompositions using one-homogeneous functionals","volume":"9","author":"Burger, Martin","year":"2016","journal-title":"SIAM J. 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