Zobrazeno 1 - 10
of 64
pro vyhledávání: '"Burges, C."'
Modern statistical machine learning (SML) methods share a major limitation with the early approaches to AI: there is no scalable way to adapt them to new domains. Human learning solves this in part by leveraging a rich, shared, updateable world model
Externí odkaz:
http://arxiv.org/abs/1612.07896
The Support Vector (SV) machine is a novel type of learning machine, based on statistical learning theory, which contains polynomial classifiers, neural networks, and radial basis function (RBF) networks as special cases. In the RBF case, the SV algo
Externí odkaz:
http://hdl.handle.net/1721.1/7180
Autor:
Burges, C., McMillan, T. M.
Publikováno v:
British Journal of Clinical Psychology. Jun2001, Vol. 40 Issue 2, p209. 6p.
Publikováno v:
DMW - Deutsche Medizinische Wochenschrift. 125:932-936
History and clinical findings A 67 year old female patient presented herself to our emergency room with paraesthesia in both hands, chronic diarrhea and continuous weight loss. From the past medical history, only an autoimmune hypothyroidism was know
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9fd018fe4e7999408fb92969fa590e0d
https://doi.org/10.1055/s-2000-7044
https://doi.org/10.1055/s-2000-7044
Publikováno v:
Advances in kernel methods: support vector learning
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1874::5a6068ee09fd5acadb38140b4178847d
https://hdl.handle.net/21.11116/0000-0005-C480-C
https://hdl.handle.net/21.11116/0000-0005-C480-C
Publikováno v:
Advances in kernel methods: support vector learning
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1874::f3d761ee8f09fac8e620b7a846ce5d71
https://hdl.handle.net/21.11116/0000-0005-C493-7
https://hdl.handle.net/21.11116/0000-0005-C493-7
Publikováno v:
Ninth Australian Conference on Neural Networks (ACNN 1998)
The last years have witnessed an increasing interest in Support Vector (SV) machines, which use Mercer kernels for efficiently performing computations in high-dimensional spaces. In pattern recognition, the SV algorithm constructs nonlinear decision
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1874::24c4dc889ae3d975bcbe7a125cecc7d2
https://hdl.handle.net/11858/00-001M-0000-0013-E9A8-1
https://hdl.handle.net/11858/00-001M-0000-0013-E9A8-1
Autor:
Burges, C., Schölkopf, B.
Publikováno v:
Advances in Neural Information Processing Systems 9
Support Vector Learning Machines (SVM) are finding application in pattern recognition, regression estimation, and operator inversion for illposed problems. Against this very general backdrop any methods for improving the generalization performance, o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1874::1655b412040e3fa36bb65de4a4d0e016
https://hdl.handle.net/11858/00-001M-0000-0013-EA22-5
https://hdl.handle.net/11858/00-001M-0000-0013-EA22-5
Publikováno v:
First International Conference on Knowledge Discovery & Data Mining (KDD-95)
We report a novel possibility for extracting a small subset of a data base which contains all the information necessary to solve a given classification task: using the Support Vector Algorithm to train three different types of handwritten digit class
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______1874::2f9a097acc0b1cfede08ecda56431a72
https://hdl.handle.net/11858/00-001M-0000-0013-EC66-3
https://hdl.handle.net/11858/00-001M-0000-0013-EC66-3