bibtype A - Abstract
ARLID 0519654
utime 20240103223428.0
mtime 20200114235959.9
title (primary) (eng) General framework for binary nonlinear classification on top samples
specification
page_count 1 s.
media_type P
serial
ARLID cav_un_epca*0519653
ISBN 9788874581016
title Book of Abstracts of the 3rd International Conference and Summer School, Numerical Computations: Theory and Algorithms
page_num 206-206
publisher
place Rende
name Centro Editoriale e Librario dell’Universit`a della Calabria
year 2019
editor
name1 Sergeyev
name2 Yaroslav D.
editor
name1 Kvasov
name2 Dmitri E.
editor
name1 Mukhametzhanov
name2 Marat S.
editor
name1 Nasso
name2 Maria Chiara
keyword binary classification
keyword duality
keyword kernels
keyword accuracy at the top
keyword ranking
keyword hypothesis testing
author (primary)
ARLID cav_un_auth*0387255
name1 Mácha
name2 Václav
institution UTIA-B
full_dept (cz) Adaptivní systémy
full_dept (eng) Adaptive Systems
department (cz) AS
department (eng) AS
country CZ
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0309054
name1 Adam
name2 Lukáš
institution UTIA-B
full_dept (cz) Matematická teorie rozhodování
full_dept Department of Decision Making Theory
department (cz) MTR
department MTR
full_dept Department of Decision Making Theory
country CZ
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
author
ARLID cav_un_auth*0101207
name1 Šmídl
name2 Václav
institution UTIA-B
full_dept (cz) Adaptivní systémy
full_dept Adaptive Systems
department (cz) AS
department AS
full_dept Department of Adaptive Systems
fullinstit Ústav teorie informace a automatizace AV ČR, v. v. i.
source
url http://library.utia.cas.cz/separaty/2019/AS/macha-0519654.pdf
cas_special
project
ARLID cav_un_auth*0374053
project_id GA18-21409S
agency GA ČR
abstract (eng) In our previous work [1], we have proposed a general framework to handle binary linear classification for top samples. Our framework includes ranking problems, accuracy at the top or hypothesis testing. We have summarized known methods, such as [2, 3, 4], belonging to this framework and proposed new ones. Note that these methods were either derived in their primal form, or they did\nnot use kernels. This forced a restriction on only linear classifiers.
action
ARLID cav_un_auth*0387256
name NUMERICAL COMPUTATIONS: THEORY AND ALGORITHMS (NUMTA–2019)
dates 20190615
mrcbC20-s 20190621
place Le Castella Village
country IT
RIV BB
FORD0 10000
FORD1 10200
FORD2 10201
reportyear 2020
mrcbC52 4 O 4o 20231122144638.3
presentation_type PR
inst_support RVO:67985556
permalink http://hdl.handle.net/11104/0304787
confidential S
arlyear 2019
mrcbTft \nSoubory v repozitáři: 0519654.pdf
mrcbU14 SCOPUS
mrcbU24 PUBMED
mrcbU34 WOS
mrcbU63 cav_un_epca*0519653 Book of Abstracts of the 3rd International Conference and Summer School, Numerical Computations: Theory and Algorithms Centro Editoriale e Librario dell’Universit`a della Calabria 2019 Rende 206 206 9788874581016
mrcbU67 340 Sergeyev Yaroslav D.
mrcbU67 340 Kvasov Dmitri E.
mrcbU67 340 Mukhametzhanov Marat S.
mrcbU67 340 Nasso Maria Chiara