Multiple-instance learning with instance selection via constructive covering algorithm

Tsinghua Science & Technology ◽

10.1109/tst.2014.6838199 ◽

2014 ◽

Vol 19 (3) ◽

pp. 285-292 ◽

Author(s):

Yanping Zhang ◽

Heng Zhang ◽

Huazhen Wei ◽

Jie Tang ◽

Shu Zhao

Keyword(s):

Multiple Instance Learning ◽

Instance Selection

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An instance selection approach to Multiple instance Learning

2009 IEEE Conference on Computer Vision and Pattern Recognition ◽

10.1109/cvpr.2009.5206655 ◽

2009 ◽

Author(s):

Zhouyu Fu ◽

Antonio Robles-Kelly

Keyword(s):

Multiple Instance Learning ◽

Instance Selection ◽

Selection Approach

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Combining example selection with instance selection to speed up multiple-instance learning

Neurocomputing ◽

10.1016/j.neucom.2013.09.008 ◽

2014 ◽

Vol 129 ◽

pp. 504-515 ◽

Author(s):

Liming Yuan ◽

Jiafeng Liu ◽

Xianglong Tang

Keyword(s):

Multiple Instance Learning ◽

Instance Selection ◽

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Revisiting Multiple-Instance Learning Via Embedded Instance Selection

AI 2008: Advances in Artificial Intelligence - Lecture Notes in Computer Science ◽

10.1007/978-3-540-89378-3_29 ◽

2008 ◽

pp. 300-310 ◽

Author(s):

James Foulds ◽

Eibe Frank

Keyword(s):

Multiple Instance Learning ◽

Instance Selection

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An Iterative Instance Selection Based Framework for Multiple-Instance Learning

2018 IEEE 30th International Conference on Tools with Artificial Intelligence (ICTAI) ◽

10.1109/ictai.2018.00121 ◽

2018 ◽

Author(s):

Liming Yuan ◽

Xianbin Wen ◽

Lu Zhao ◽

Haixia Xu

Keyword(s):

Multiple Instance Learning ◽

Instance Selection

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Robust multiple-instance learning ensembles using random subspace instance selection

Pattern Recognition ◽

10.1016/j.patcog.2016.03.035 ◽

2016 ◽

Vol 58 ◽

pp. 83-99 ◽

Author(s):

Marc-André Carbonneau ◽

Eric Granger ◽

Alexandre J. Raymond ◽

Ghyslain Gagnon

Keyword(s):

Multiple Instance Learning ◽

Instance Selection ◽

Random Subspace ◽

Learning Ensembles

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MILKDE: A new approach for multiple instance learning based on positive instance selection and kernel density estimation

Engineering Applications of Artificial Intelligence ◽

10.1016/j.engappai.2016.12.015 ◽

2017 ◽

Vol 59 ◽

pp. 196-204 ◽

Author(s):

A.W.C. Faria ◽

F.G.F. Coelho ◽

A.M. Silva ◽

H.P. Rocha ◽

G.M. Almeida ◽

...

Keyword(s):

Density Estimation ◽

Kernel Density Estimation ◽

Kernel Density ◽

Multiple Instance Learning ◽

Positive Instance ◽

Instance Selection ◽

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Multiple-Instance Learning with Evolutionary Instance Selection

Database Systems for Advanced Applications - Lecture Notes in Computer Science ◽

10.1007/978-3-319-32025-0_15 ◽

2016 ◽

pp. 229-241 ◽

Author(s):

Yongshan Zhang ◽

Jia Wu ◽

Chuan Zhou ◽

Peng Zhang ◽

Zhihua Cai

Keyword(s):

Multiple Instance Learning ◽

Instance Selection

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MILES: Multiple-Instance Learning via Embedded Instance Selection

IEEE Transactions on Pattern Analysis and Machine Intelligence ◽

10.1109/tpami.2006.248 ◽

2006 ◽

Vol 28 (12) ◽

pp. 1931-1947 ◽

Author(s):

Yixin Chen ◽

Jinbo Bi ◽

J.Z. Wang

Keyword(s):

Multiple Instance Learning ◽

Instance Selection

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Multiple instance learning based on positive instance selection and bag structure construction

Pattern Recognition Letters ◽

10.1016/j.patrec.2013.11.013 ◽

2014 ◽

Vol 40 ◽

pp. 19-26 ◽

Author(s):

Zhan Li ◽

Guo-Hua Geng ◽

Jun Feng ◽

Jin-ye Peng ◽

Chao Wen ◽

...

Keyword(s):

Multiple Instance Learning ◽

Positive Instance ◽

Instance Selection

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Multiple- Instance Learning with Empirical Estimation Guided Instance Selection

2018 24th International Conference on Pattern Recognition (ICPR) ◽

10.1109/icpr.2018.8546304 ◽

2018 ◽

Author(s):

Liming Yuan ◽

Xianbin Wen ◽

Haixia Xu ◽

Lu Zhao

Keyword(s):

Multiple Instance Learning ◽

Instance Selection ◽

Empirical Estimation

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