Domain Adaptation Theory: Available Theoretical Results
Advances in Domain Adaptation Theory gives current, state-of-the-art results on transfer learning, with a particular focus placed on domain adaptation from a theoretical point-of-view. The book begins with a brief overview of the most popular concepts used to provide generalization guarantees, inclu...
Uloženo v:
| Hlavní autoři: | , , , , |
|---|---|
| Médium: | E-kniha |
| Jazyk: | angličtina |
| Vydáno: |
Elsevier
23.08.2019
|
| Témata: | |
| ISBN: | 178548236X, 9781785482366 |
| On-line přístup: | Získat plný text |
| Tagy: |
Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
|
| Abstract | Advances in Domain Adaptation Theory gives current, state-of-the-art results on transfer learning, with a particular focus placed on domain adaptation from a theoretical point-of-view. The book begins with a brief overview of the most popular concepts used to provide generalization guarantees, including sections on Vapnik-Chervonenkis (VC), Rademacher, PAC-Bayesian, Robustness and Stability based bounds. In addition, the book explains domain adaptation problem and describes the four major families of theoretical results that exist in the literature, including the Divergence based bounds. Next, PAC-Bayesian bounds are discussed, including the original PAC-Bayesian bounds for domain adaptation and their updated version. Additional sections present generalization guarantees based on the robustness and stability properties of the learning algorithm. |
|---|---|
| AbstractList | Advances in Domain Adaptation Theory gives current, state-of-the-art results on transfer learning, with a particular focus placed on domain adaptation from a theoretical point-of-view. The book begins with a brief overview of the most popular concepts used to provide generalization guarantees, including sections on Vapnik-Chervonenkis (VC), Rademacher, PAC-Bayesian, Robustness and Stability based bounds. In addition, the book explains domain adaptation problem and describes the four major families of theoretical results that exist in the literature, including the Divergence based bounds. Next, PAC-Bayesian bounds are discussed, including the original PAC-Bayesian bounds for domain adaptation and their updated version. Additional sections present generalization guarantees based on the robustness and stability properties of the learning algorithm. |
| Author | Redko, Ievgen Bennani, Younes Habrard, Amaury Morvant, Emilie Sebban, Marc |
| Author_xml | – sequence: 1 fullname: Redko, Ievgen – sequence: 2 fullname: Morvant, Emilie – sequence: 3 fullname: Habrard, Amaury – sequence: 4 fullname: Sebban, Marc – sequence: 5 fullname: Bennani, Younes |
| BookMark | eNpVj0tLw0AURkesoK35D9m6CNx5ZW7dhfqoUBAki-7KncwNjR0z4sSK_16hblx9cBbn8M3FbEwjn4li6RAAJShtnDwXc-nQGlS63l6KIudXAFDW1NbClXB36Y2GsWwCvU80DWks2z2nj-_bsjnSEMlHPhGeho5i-cL5M075Wlz0FDMXf7sQ7cN9u1pXm-fHp1WzqQglVlKCN8Fg7ci43jnP1hMGDgFq2S21sspZgg5l5zy42lvysmeDQaPqUeqFuDlpKR_4K-_Tb3p3jOxTOuTdv6P6B6AtR50 |
| ContentType | eBook |
| DEWEY | 006.31 |
| DatabaseTitleList | |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Computer Science |
| EISBN | 9780081023471 0081023472 |
| ExternalDocumentID | 9780081023471 |
| GroupedDBID | 20A AAAAS AABBV AAJFB AAJIE AAKZG AALRI AAWMN AAXUO AAZNM ABGWT ABLXK ABQQC ACDGK ACKCA ADCEY AEIUV AEYWH ALBLE ALMA_UNASSIGNED_HOLDINGS AOVBA BBABE BGHEG CZZ HGY SDK |
| ID | FETCH-LOGICAL-a818-110b4d4867a47f77be5ba8dedd061c9325275a0c81c7b076b5ab1fe48d382f813 |
| ISBN | 178548236X 9781785482366 |
| IngestDate | Fri Nov 08 05:41:09 EST 2024 |
| IsPeerReviewed | false |
| IsScholarly | false |
| Language | English |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-a818-110b4d4867a47f77be5ba8dedd061c9325275a0c81c7b076b5ab1fe48d382f813 |
| PageCount | 1 |
| ParticipantIDs | askewsholts_vlebooks_9780081023471 |
| PublicationCentury | 2000 |
| PublicationDate | 2019-08-23 |
| PublicationDateYYYYMMDD | 2019-08-23 |
| PublicationDate_xml | – month: 08 year: 2019 text: 2019-08-23 day: 23 |
| PublicationDecade | 2010 |
| PublicationYear | 2019 |
| Publisher | Elsevier |
| Publisher_xml | – name: Elsevier |
| SSID | ssj0002546550 |
| Score | 2.1208696 |
| Snippet | Advances in Domain Adaptation Theory gives current, state-of-the-art results on transfer learning, with a particular focus placed on domain adaptation from a... |
| SourceID | askewsholts |
| SourceType | Aggregation Database |
| SubjectTerms | Computer algorithms Machine learning |
| Title | Domain Adaptation Theory: Available Theoretical Results |
| URI | https://www.vlebooks.com/vleweb/product/openreader?id=none&isbn=9780081023471 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV07b4MwELbapEOz9K2-haquSLztdKuS9KE2UdUyZItsbCoUAlEgKD-_ZyBAMrVDFwssZIk7Y3_34e8OoXuPUJgn3FDl9gsBig7fnAMxj9-VNa48nTM_r1ryjkcjMh53P8qsC0leTgBHEVmtuvN_dTX0gbOldPYP7q4GhQ64BqdDC26HdgsRV7eFx_vxjEr2gtN5eYSwEN7n3F9GgzBXSbkN5eKnSJZhWp92F3yaM6evIvuuJWLDeAFwO1-sB7MgDOqpQGWoXRDTMj1Rxc5_CcYKYnUIxm0SC1LLRNRC-1uwXeXWvBFw6phAiGOYzlb66nhdHwEQBqAAS6r6d7ED0XD7sdd_fqtoL5l-H4IiKbFbD1XmQaqH7qAOTaawxsP6nyaN7d49RG0hNSBHaEdEx-hgXflCKRfCE4QLWyu1rZXC1g9KZWmlYWmltPQpcp8Gbu9FLUtQqBSQjArYiFlcJiWkFvYxZsJmlHDBOcAgD6CvbWCbah7RPcw07DCbMt0XFuEmMXyim2eoFcWROEeKaVEAx4xxS7Ms4QmimbKgo-4Q28eAky7QXeOlJ1mY_yxPJhtGvfzNQ1dov3bnNWqli6W4QXtelgbJ4rZ0yA8IPhr2 |
| linkProvider | Elsevier |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=book&rft.title=Domain+Adaptation+Theory%3A+Available+Theoretical+Results&rft.au=Redko%2C+Ievgen&rft.au=Morvant%2C+Emilie&rft.au=Habrard%2C+Amaury&rft.au=Sebban%2C+Marc&rft.date=2019-08-23&rft.pub=Elsevier&rft.isbn=9781785482366&rft.externalDocID=9780081023471 |
| thumbnail_m | http://cvtisr.summon.serialssolutions.com/2.0.0/image/custom?url=https%3A%2F%2Fvle.dmmserver.com%2Fmedia%2F640%2F97800810%2F9780081023471.jpg |