Mathematical Foundations of Machine Learning (Record no. 3548)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02044nas a22003015i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 3059-3492 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | DE-He213 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20260610082520.0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION | |
| fixed length control field | cr nn 008mamaa |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 240918s||||||||sz uu poo|||||| b|EN |d |
| 022 ## - INTERNATIONAL STANDARD SERIAL NUMBER | |
| International Standard Serial Number | 3059-3492 |
| 024 7# - OTHER STANDARD IDENTIFIER | |
| Standard number or code | 44439 |
| Source of number or code | local |
| 210 10 - ABBREVIATED TITLE | |
| Abbreviated title | Math. Found. Mach. Learn. |
| 245 10 - TITLE STATEMENT | |
| Title | Mathematical Foundations of Machine Learning |
| Medium | [electronic resource] / |
| Statement of responsibility, etc. | edited by Helmut Bölcskei. |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE | |
| Place of production, publication, distribution, manufacture | Cham : |
| Name of producer, publisher, distributor, manufacturer | Springer International Publishing : |
| -- | Imprint: Springer. |
| 300 ## - online resource | |
| Other physical details | online resource. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | Mathematical Foundations of Machine Learning (MFML) is a forum for the publication of papers concerned with all pure and applied mathematical aspects of machine learning, with a particular focus on foundational work. Areas of interest include, inter alia, functional analysis, approximation theory, harmonic analysis, partial differential equations, combinatorics, probability theory, statistics, geometry, algebra, analytic number theory, complex analysis, linear algebra, group theory, representation theory, theoretical computer science, complexity theory, numerical analysis, algebraic geometry, mathematical logic, geometric measure theory, and optimization theory. All papers must be characterized by originality and mathematical rigour. We explicitly encourage papers of conceptual value residing in the synthesis of mathematical theories and their application to fundamental problems in machine learning theory and practice. Survey papers are welcome as well and must exhibit originality in the synthesis of the material and their vantage point. . |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Mathematics. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Mathematics. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Machine learning. |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Mathematics. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Mathematics and Computing. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name entry element | Machine Learning. |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Bölcskei, Helmut. |
| Relator term | editor. |
| Relationship | edt |
| -- | http://id.loc.gov/vocabulary/relators/edt |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | SpringerLink (Online service) |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | <a href="http://link.springer.com/journal/44439">http://link.springer.com/journal/44439</a> |
| Public note | Hybrid |
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