Query by committee, linear separation and random walks

Shai Fine; Ran Gilad-Bachrach; Eli Shamir

doi:10.1016/S0304-3975(01)00079-2

Query by committee, linear separation and random walks

Shai Fine^*
, Ran Gilad-Bachrach
, Eli Shamir

^*Corresponding author for this work

Einstein Institute of Mathematics

Research output: Contribution to journal › Conference article › peer-review

27 Scopus citations

Abstract

The problems involved in the implementation of machine learning by minimizing sample-complexity were studied. These problems were solved in the field of computational geometry based on random walks. A connection between random walks and machine learning notations such as support vector machines was also investigated.

Original language	English
Pages (from-to)	25-51
Number of pages	27
Journal	Theoretical Computer Science
Volume	284
Issue number	1
DOIs	https://doi.org/10.1016/S0304-3975(01)00079-2
State	Published - 6 Jul 2002
Event	Computing Learining Theory - Nordkirchen, Germany Duration: 29 Mar 1999 → 31 Mar 1999

Keywords

Active learning
Experimental design
Labeled and unlabelled data
Selective sampling
Volume approximation

Access to Document

10.1016/S0304-3975(01)00079-2

Cite this

@article{8a54b6c5b8b24d8fa742b01934f2bf2a,

title = "Query by committee, linear separation and random walks",

abstract = "The problems involved in the implementation of machine learning by minimizing sample-complexity were studied. These problems were solved in the field of computational geometry based on random walks. A connection between random walks and machine learning notations such as support vector machines was also investigated.",

keywords = "Active learning, Experimental design, Labeled and unlabelled data, Selective sampling, Volume approximation",

author = "Shai Fine and Ran Gilad-Bachrach and Eli Shamir",

year = "2002",

month = jul,

day = "6",

doi = "10.1016/S0304-3975(01)00079-2",

language = "אנגלית",

volume = "284",

pages = "25--51",

journal = "Theoretical Computer Science",

issn = "0304-3975",

publisher = "Elsevier B.V.",

number = "1",

note = "Computing Learining Theory ; Conference date: 29-03-1999 Through 31-03-1999",

}

TY - JOUR

T1 - Query by committee, linear separation and random walks

AU - Fine, Shai

AU - Gilad-Bachrach, Ran

AU - Shamir, Eli

PY - 2002/7/6

Y1 - 2002/7/6

N2 - The problems involved in the implementation of machine learning by minimizing sample-complexity were studied. These problems were solved in the field of computational geometry based on random walks. A connection between random walks and machine learning notations such as support vector machines was also investigated.

AB - The problems involved in the implementation of machine learning by minimizing sample-complexity were studied. These problems were solved in the field of computational geometry based on random walks. A connection between random walks and machine learning notations such as support vector machines was also investigated.

KW - Active learning

KW - Experimental design

KW - Labeled and unlabelled data

KW - Selective sampling

KW - Volume approximation

UR - https://www.scopus.com/pages/publications/0037031027

U2 - 10.1016/S0304-3975(01)00079-2

DO - 10.1016/S0304-3975(01)00079-2

M3 - ???researchoutput.researchoutputtypes.contributiontojournal.conferencearticle???

AN - SCOPUS:0037031027

SN - 0304-3975

VL - 284

SP - 25

EP - 51

JO - Theoretical Computer Science

JF - Theoretical Computer Science

IS - 1

T2 - Computing Learining Theory

Y2 - 29 March 1999 through 31 March 1999

ER -

Query by committee, linear separation and random walks

Abstract

Keywords

Access to Document

Other files and links

Fingerprint

Cite this