Optimization, Discrete Mathematics and Applications to Data Sciences:
This book delves into the dynamic intersection of optimization and discrete mathematics, offering a comprehensive exploration of their applications in data sciences. Through a collection of high-quality papers, readers will gain insights into cutting-edge research and methodologies that address comp...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Cham
Springer
2025
|
| Schriftenreihe: | Springer Optimization and Its Applications
220 |
| Schlagworte: | |
| Zusammenfassung: | This book delves into the dynamic intersection of optimization and discrete mathematics, offering a comprehensive exploration of their applications in data sciences. Through a collection of high-quality papers, readers will gain insights into cutting-edge research and methodologies that address complex problems across a wide array of topics.The chapters cover an impressive range of subjects, including advances in the study of polynomials, combinatorial identities, and global optimization algorithms. Readers will encounter innovative approaches to predictive models for non-performing loans, rainbow greedy matching algorithms, and the cost of detection in interaction testing. The book also examines critical issues such as demand aggregation, mid-term energy planning, and minimum-cost energy flow. Contributions from expert authors provide a deep dive into multilevel low-rank matrices, the protection of medical image authenticity, and the mathematical intricacies of the Braess paradox. This volume invites readers to explore diverse perspectives and theoretical insights that are both practical and forward-thinking.This publication is an invaluable resource for graduate students and advanced researchers in the fields of optimization and discrete mathematics. It is particularly beneficial for those interested in their applications within data sciences. Academics across these disciplines will find the book's content relevant to their work, while practitioners seeking to apply these concepts in industry will appreciate its practical case studies. Whether you are a scholar or a professional, this book offers a wealth of knowledge that bridges theory with real-world applications |
| Beschreibung: | X, 217 p. 63 illus., 54 illus. in color. - This book delves into the dynamic intersection of optimization and discrete mathematics, offering a comprehensive exploration of their applications in data sciences. Through a collection of high-quality papers, readers will gain insights into cutting-edge research and methodologies that address complex problems across a wide array of topics.The chapters cover an impressive range of subjects, including advances in the study of polynomials, combinatorial identities, and global optimization algorithms. Readers will encounter innovative approaches to predictive models for non-performing loans, rainbow greedy matching algorithms, and the cost of detection in interaction testing. The book also examines critical issues such as demand aggregation, mid-term energy planning, and minimum-cost energy flow. Contributions from expert authors provide a deep dive into multilevel low-rank matrices, the protection of medical image authenticity, and the mathematical intricacies of the Braess paradox. This volume invites readers to explore diverse perspectives and theoretical insights that are both practical and forward-thinking.This publication is an invaluable resource for graduate students and advanced researchers in the fields of optimization and discrete mathematics. It is particularly beneficial for those interested in their applications within data sciences. Academics across these disciplines will find the book's content relevant to their work, while practitioners seeking to apply these concepts in industry will appreciate its practical case studies. Whether you are a scholar or a professional, this book offers a wealth of knowledge that bridges theory with real-world applications |
| Beschreibung: | 237 Seiten 235 mm |
| ISBN: | 9783031783685 |
Internformat
MARC
| LEADER | 00000nam a2200000 c 4500 | ||
|---|---|---|---|
| 001 | BV050173428 | ||
| 003 | DE-604 | ||
| 007 | t| | ||
| 008 | 250218s2025 xx |||| 00||| eng d | ||
| 020 | |a 9783031783685 |9 978-3-031-78368-5 | ||
| 024 | 3 | |a 9783031783685 | |
| 035 | |a (DE-599)BVBBV050173428 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-29T | ||
| 100 | 1 | |a Nikeghbali, Ashkan |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Optimization, Discrete Mathematics and Applications to Data Sciences |
| 264 | 1 | |a Cham |b Springer |c 2025 | |
| 300 | |a 237 Seiten |c 235 mm | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 0 | |a Springer Optimization and Its Applications |v 220 | |
| 500 | |a X, 217 p. 63 illus., 54 illus. in color. - This book delves into the dynamic intersection of optimization and discrete mathematics, offering a comprehensive exploration of their applications in data sciences. Through a collection of high-quality papers, readers will gain insights into cutting-edge research and methodologies that address complex problems across a wide array of topics.The chapters cover an impressive range of subjects, including advances in the study of polynomials, combinatorial identities, and global optimization algorithms. Readers will encounter innovative approaches to predictive models for non-performing loans, rainbow greedy matching algorithms, and the cost of detection in interaction testing. The book also examines critical issues such as demand aggregation, mid-term energy planning, and minimum-cost energy flow. Contributions from expert authors provide a deep dive into multilevel low-rank matrices, the protection of medical image authenticity, and the mathematical intricacies of the Braess paradox. This volume invites readers to explore diverse perspectives and theoretical insights that are both practical and forward-thinking.This publication is an invaluable resource for graduate students and advanced researchers in the fields of optimization and discrete mathematics. It is particularly beneficial for those interested in their applications within data sciences. Academics across these disciplines will find the book's content relevant to their work, while practitioners seeking to apply these concepts in industry will appreciate its practical case studies. Whether you are a scholar or a professional, this book offers a wealth of knowledge that bridges theory with real-world applications | ||
| 520 | |a This book delves into the dynamic intersection of optimization and discrete mathematics, offering a comprehensive exploration of their applications in data sciences. Through a collection of high-quality papers, readers will gain insights into cutting-edge research and methodologies that address complex problems across a wide array of topics.The chapters cover an impressive range of subjects, including advances in the study of polynomials, combinatorial identities, and global optimization algorithms. Readers will encounter innovative approaches to predictive models for non-performing loans, rainbow greedy matching algorithms, and the cost of detection in interaction testing. The book also examines critical issues such as demand aggregation, mid-term energy planning, and minimum-cost energy flow. Contributions from expert authors provide a deep dive into multilevel low-rank matrices, the protection of medical image authenticity, and the mathematical intricacies of the Braess paradox. This volume invites readers to explore diverse perspectives and theoretical insights that are both practical and forward-thinking.This publication is an invaluable resource for graduate students and advanced researchers in the fields of optimization and discrete mathematics. It is particularly beneficial for those interested in their applications within data sciences. Academics across these disciplines will find the book's content relevant to their work, while practitioners seeking to apply these concepts in industry will appreciate its practical case studies. Whether you are a scholar or a professional, this book offers a wealth of knowledge that bridges theory with real-world applications | ||
| 650 | 4 | |a bicssc | |
| 650 | 4 | |a bicssc | |
| 650 | 4 | |a bicssc | |
| 650 | 4 | |a bicssc | |
| 650 | 4 | |a bicssc | |
| 650 | 4 | |a bisacsh | |
| 650 | 4 | |a bisacsh | |
| 650 | 4 | |a bisacsh | |
| 650 | 4 | |a bisacsh | |
| 650 | 4 | |a bisacsh | |
| 650 | 4 | |a Discrete mathematics | |
| 650 | 4 | |a Number theory | |
| 650 | 4 | |a System theory | |
| 650 | 4 | |a Control theory | |
| 650 | 4 | |a Convex geometry | |
| 650 | 4 | |a Discrete geometry | |
| 650 | 4 | |a Mathematical optimization | |
| 653 | |a Hardcover, Softcover / Mathematik/Sonstiges | ||
| 700 | 1 | |a Pardalos, Panos M. |e Sonstige |4 oth | |
| 700 | 1 | |a Rassias, Michael Th |e Sonstige |4 oth | |
| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-035509311 | |
Datensatz im Suchindex
| _version_ | 1824508626314723328 |
|---|---|
| adam_text | |
| any_adam_object | |
| author | Nikeghbali, Ashkan |
| author_facet | Nikeghbali, Ashkan |
| author_role | aut |
| author_sort | Nikeghbali, Ashkan |
| author_variant | a n an |
| building | Verbundindex |
| bvnumber | BV050173428 |
| ctrlnum | (DE-599)BVBBV050173428 |
| format | Book |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>00000nam a2200000 c 4500</leader><controlfield tag="001">BV050173428</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="007">t|</controlfield><controlfield tag="008">250218s2025 xx |||| 00||| eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9783031783685</subfield><subfield code="9">978-3-031-78368-5</subfield></datafield><datafield tag="024" ind1="3" ind2=" "><subfield code="a">9783031783685</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV050173428</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-29T</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Nikeghbali, Ashkan</subfield><subfield code="e">Verfasser</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Optimization, Discrete Mathematics and Applications to Data Sciences</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Cham</subfield><subfield code="b">Springer</subfield><subfield code="c">2025</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">237 Seiten</subfield><subfield code="c">235 mm</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="0" ind2=" "><subfield code="a">Springer Optimization and Its Applications</subfield><subfield code="v">220</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">X, 217 p. 63 illus., 54 illus. in color. - This book delves into the dynamic intersection of optimization and discrete mathematics, offering a comprehensive exploration of their applications in data sciences. Through a collection of high-quality papers, readers will gain insights into cutting-edge research and methodologies that address complex problems across a wide array of topics.The chapters cover an impressive range of subjects, including advances in the study of polynomials, combinatorial identities, and global optimization algorithms. Readers will encounter innovative approaches to predictive models for non-performing loans, rainbow greedy matching algorithms, and the cost of detection in interaction testing. The book also examines critical issues such as demand aggregation, mid-term energy planning, and minimum-cost energy flow. Contributions from expert authors provide a deep dive into multilevel low-rank matrices, the protection of medical image authenticity, and the mathematical intricacies of the Braess paradox. This volume invites readers to explore diverse perspectives and theoretical insights that are both practical and forward-thinking.This publication is an invaluable resource for graduate students and advanced researchers in the fields of optimization and discrete mathematics. It is particularly beneficial for those interested in their applications within data sciences. Academics across these disciplines will find the book's content relevant to their work, while practitioners seeking to apply these concepts in industry will appreciate its practical case studies. Whether you are a scholar or a professional, this book offers a wealth of knowledge that bridges theory with real-world applications</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">This book delves into the dynamic intersection of optimization and discrete mathematics, offering a comprehensive exploration of their applications in data sciences. Through a collection of high-quality papers, readers will gain insights into cutting-edge research and methodologies that address complex problems across a wide array of topics.The chapters cover an impressive range of subjects, including advances in the study of polynomials, combinatorial identities, and global optimization algorithms. Readers will encounter innovative approaches to predictive models for non-performing loans, rainbow greedy matching algorithms, and the cost of detection in interaction testing. The book also examines critical issues such as demand aggregation, mid-term energy planning, and minimum-cost energy flow. Contributions from expert authors provide a deep dive into multilevel low-rank matrices, the protection of medical image authenticity, and the mathematical intricacies of the Braess paradox. This volume invites readers to explore diverse perspectives and theoretical insights that are both practical and forward-thinking.This publication is an invaluable resource for graduate students and advanced researchers in the fields of optimization and discrete mathematics. It is particularly beneficial for those interested in their applications within data sciences. Academics across these disciplines will find the book's content relevant to their work, while practitioners seeking to apply these concepts in industry will appreciate its practical case studies. Whether you are a scholar or a professional, this book offers a wealth of knowledge that bridges theory with real-world applications</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">bicssc</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">bicssc</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">bicssc</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">bicssc</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">bicssc</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">bisacsh</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">bisacsh</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">bisacsh</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">bisacsh</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">bisacsh</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Discrete mathematics</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Number theory</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">System theory</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Control theory</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Convex geometry </subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Discrete geometry</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Mathematical optimization</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Hardcover, Softcover / Mathematik/Sonstiges</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Pardalos, Panos M.</subfield><subfield code="e">Sonstige</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Rassias, Michael Th</subfield><subfield code="e">Sonstige</subfield><subfield code="4">oth</subfield></datafield><datafield tag="943" ind1="1" ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-035509311</subfield></datafield></record></collection> |
| id | DE-604.BV050173428 |
| illustrated | Not Illustrated |
| indexdate | 2025-02-19T17:43:36Z |
| institution | BVB |
| isbn | 9783031783685 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-035509311 |
| open_access_boolean | |
| owner | DE-29T |
| owner_facet | DE-29T |
| physical | 237 Seiten 235 mm |
| publishDate | 2025 |
| publishDateSearch | 2025 |
| publishDateSort | 2025 |
| publisher | Springer |
| record_format | marc |
| series2 | Springer Optimization and Its Applications |
| spelling | Nikeghbali, Ashkan Verfasser aut Optimization, Discrete Mathematics and Applications to Data Sciences Cham Springer 2025 237 Seiten 235 mm txt rdacontent n rdamedia nc rdacarrier Springer Optimization and Its Applications 220 X, 217 p. 63 illus., 54 illus. in color. - This book delves into the dynamic intersection of optimization and discrete mathematics, offering a comprehensive exploration of their applications in data sciences. Through a collection of high-quality papers, readers will gain insights into cutting-edge research and methodologies that address complex problems across a wide array of topics.The chapters cover an impressive range of subjects, including advances in the study of polynomials, combinatorial identities, and global optimization algorithms. Readers will encounter innovative approaches to predictive models for non-performing loans, rainbow greedy matching algorithms, and the cost of detection in interaction testing. The book also examines critical issues such as demand aggregation, mid-term energy planning, and minimum-cost energy flow. Contributions from expert authors provide a deep dive into multilevel low-rank matrices, the protection of medical image authenticity, and the mathematical intricacies of the Braess paradox. This volume invites readers to explore diverse perspectives and theoretical insights that are both practical and forward-thinking.This publication is an invaluable resource for graduate students and advanced researchers in the fields of optimization and discrete mathematics. It is particularly beneficial for those interested in their applications within data sciences. Academics across these disciplines will find the book's content relevant to their work, while practitioners seeking to apply these concepts in industry will appreciate its practical case studies. Whether you are a scholar or a professional, this book offers a wealth of knowledge that bridges theory with real-world applications This book delves into the dynamic intersection of optimization and discrete mathematics, offering a comprehensive exploration of their applications in data sciences. Through a collection of high-quality papers, readers will gain insights into cutting-edge research and methodologies that address complex problems across a wide array of topics.The chapters cover an impressive range of subjects, including advances in the study of polynomials, combinatorial identities, and global optimization algorithms. Readers will encounter innovative approaches to predictive models for non-performing loans, rainbow greedy matching algorithms, and the cost of detection in interaction testing. The book also examines critical issues such as demand aggregation, mid-term energy planning, and minimum-cost energy flow. Contributions from expert authors provide a deep dive into multilevel low-rank matrices, the protection of medical image authenticity, and the mathematical intricacies of the Braess paradox. This volume invites readers to explore diverse perspectives and theoretical insights that are both practical and forward-thinking.This publication is an invaluable resource for graduate students and advanced researchers in the fields of optimization and discrete mathematics. It is particularly beneficial for those interested in their applications within data sciences. Academics across these disciplines will find the book's content relevant to their work, while practitioners seeking to apply these concepts in industry will appreciate its practical case studies. Whether you are a scholar or a professional, this book offers a wealth of knowledge that bridges theory with real-world applications bicssc bisacsh Discrete mathematics Number theory System theory Control theory Convex geometry Discrete geometry Mathematical optimization Hardcover, Softcover / Mathematik/Sonstiges Pardalos, Panos M. Sonstige oth Rassias, Michael Th Sonstige oth |
| spellingShingle | Nikeghbali, Ashkan Optimization, Discrete Mathematics and Applications to Data Sciences bicssc bisacsh Discrete mathematics Number theory System theory Control theory Convex geometry Discrete geometry Mathematical optimization |
| title | Optimization, Discrete Mathematics and Applications to Data Sciences |
| title_auth | Optimization, Discrete Mathematics and Applications to Data Sciences |
| title_exact_search | Optimization, Discrete Mathematics and Applications to Data Sciences |
| title_full | Optimization, Discrete Mathematics and Applications to Data Sciences |
| title_fullStr | Optimization, Discrete Mathematics and Applications to Data Sciences |
| title_full_unstemmed | Optimization, Discrete Mathematics and Applications to Data Sciences |
| title_short | Optimization, Discrete Mathematics and Applications to Data Sciences |
| title_sort | optimization discrete mathematics and applications to data sciences |
| topic | bicssc bisacsh Discrete mathematics Number theory System theory Control theory Convex geometry Discrete geometry Mathematical optimization |
| topic_facet | bicssc bisacsh Discrete mathematics Number theory System theory Control theory Convex geometry Discrete geometry Mathematical optimization |
| work_keys_str_mv | AT nikeghbaliashkan optimizationdiscretemathematicsandapplicationstodatasciences AT pardalospanosm optimizationdiscretemathematicsandapplicationstodatasciences AT rassiasmichaelth optimizationdiscretemathematicsandapplicationstodatasciences |