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Beyond Banditron: A Conservative and Efficient Reduction for Online Multiclass Prediction with Bandit Setting Model

Guangyun Chen, Gang Chen, Jianwen Zhang, Shuo Chen, Changshui Zhang
2009 2009 Ninth IEEE International Conference on Data Mining  

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In this paper, we consider a recently proposed supervised learning problem, called online multiclass prediction with bandit setting model.  ...  First, we reduce the multiclass prediction problem to binary based on Conservative one-versusall others Reduction scheme; Then Online Passive-Aggressive Algorithm is embedded as binary learning algorithm  ...  This paper provides a new perspective for online multiclass prediction with bandit setting model.  ... 
doi:10.1109/icdm.2009.36 dblp:conf/icdm/ChenCZCZ09 fatcat:duiwvhsjxzanrppwbd63yfo3f4
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Guangyun Chen, Gang Chen, Jianwen Zhang, Shuo Chen, Changshui Zhang. "Beyond Banditron: A Conservative and Efficient Reduction for Online Multiclass Prediction with Bandit Setting Model." 2009 Ninth IEEE International Conference on Data Mining (2009) 71-80

ICDM 2009 Program

2009 2009 Ninth IEEE International Conference on Data Mining  

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SL2 Supervised Learning #2 Beyond Banditron: A Conservative and Efficient Reduction for Online Multiclass Prediction with Bandit Setting Mode Guangyun Chen, Gang Chen, Jianwen Zhang, Shuo Chen, and  ...  Predicting Online Trusts using Trust Antecedent Framework Ee-Peng Lim, Viet-An Nguyen, Aixin Sun, Jing Jiang, and Hwee Hoon Tan Short Wednesday 4:30-6:40PM WSN Web and Social Network Efficient Award  ... 
doi:10.1109/icdm.2009.151 fatcat:xvzjtpkkvbh25k5lmjslaf2jdi
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"ICDM 2009 Program." 2009 Ninth IEEE International Conference on Data Mining (2009)

Bandit Multiclass Linear Classification: Efficient Algorithms for the Separable Case [article]

Alina Beygelzimer, Dávid Pál, Balázs Szörényi, Devanathan Thiruvenkatachari, Chen-Yu Wei, Chicheng Zhang
2019 arXiv   pre-print

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2019 pre-print arXiv:1902.02244v1 fatcat:yiestuwrrjcu5lkmhikv7ffria
We study the problem of efficient online multiclass linear classification with bandit feedback, where all examples belong to one of K classes and lie in the d-dimensional Euclidean space.  ...  Previous works have left open the challenge of designing efficient algorithms with finite mistake bounds when the data is linearly separable by a margin γ.  ...  Guangyun Chen, Gang Chen, Jianwen Zhang, Shuo Chen, and Changshui Zhang. Beyond banditron: A conservative and efficient reduction for online multiclass prediction with bandit setting model.  ... 
arXiv:1902.02244v2 fatcat:tlwtx7ojs5hw5j46jm6olfehwu
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Alina Beygelzimer, Dávid Pál, Balázs Szörényi, Devanathan Thiruvenkatachari, Chen-Yu Wei, Chicheng Zhang. "Bandit Multiclass Linear Classification: Efficient Algorithms for the Separable Case." arXiv (2019)