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Volumn 2, Issue , 2012, Pages 1151-1159

On multilabel classification and ranking with partial feedback

Author keywords

[No Author keywords available]

Indexed keywords

DESCENT METHOD; EXPLORATION AND EXPLOITATION; MULTI-LABEL; MULTI-LABEL CLASSIFICATIONS; PARTIAL FEEDBACK; PARTIAL INFORMATION; REAL-WORLD; REGRET BOUNDS;

EID: 84877760626     PISSN: 10495258     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (14)

References (23)
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    • Stochastic linear optimization under bandit feedback
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    • Dani, V.1    Hayes, T.2    Kakade, S.3
  • 7
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    • Parametric bandits: The generalized linear case
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  • 8
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    • An efficient boosting algorithm for combining preferences
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  • 10
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    • Online submodular minimization
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    • Newtron: An efficient bandit algorithm for online multiclass prediction
    • E. Hazan and S. Kale. Newtron: an efficient bandit algorithm for online multiclass prediction. In NIPS, 2011.
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    • Hazan, E.1    Kale, S.2
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    • Efficient bandit algorithms for online multiclass prediction
    • S. Kakade, S. Shalev-Shwartz, and A. Tewari. Efficient bandit algorithms for online multiclass prediction. In 25th ICML, 2008.
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    • Online structured prediction via coactive learning
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    • P. Shivaswamy and T. Joachims. Online structured prediction via coactive learning. In 29th ICML, 2012, to appear.
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.