Sciweavers

ICML
2010
IEEE
14 years 18 days ago
Boosting Classifiers with Tightened L0-Relaxation Penalties
We propose a novel boosting algorithm which improves on current algorithms for weighted voting classification by striking a better balance between classification accuracy and the ...
Noam Goldberg, Jonathan Eckstein
ICONIP
2004
14 years 27 days ago
The Most Robust Loss Function for Boosting
Boosting algorithm is understood as the gradient descent algorithm of a loss function. It is often pointed out that the typical boosting algorithm, Adaboost, is seriously affected ...
Takafumi Kanamori, Takashi Takenouchi, Shinto Eguc...
EMNLP
2004
14 years 28 days ago
A Boosting Algorithm for Classification of Semi-Structured Text
The focus of research in text classification has expanded from simple topic identification to more challenging tasks such as opinion/modality identification. Unfortunately, the la...
Taku Kudo, Yuji Matsumoto
IJCAI
2007
14 years 29 days ago
Real Boosting a la Carte with an Application to Boosting Oblique Decision Tree
In the past ten years, boosting has become a major field of machine learning and classification. This paper brings contributions to its theory and algorithms. We first unify a ...
Claudia Henry, Richard Nock, Frank Nielsen
EUROCOLT
1995
Springer
14 years 3 months ago
A decision-theoretic generalization of on-line learning and an application to boosting
k. The model we study can be interpreted as a broad, abstract extension of the well-studied on-line prediction model to a general decision-theoretic setting. We show that the multi...
Yoav Freund, Robert E. Schapire
COLT
1999
Springer
14 years 3 months ago
An Adaptive Version of the Boost by Majority Algorithm
We propose a new boosting algorithm. This boosting algorithm is an adaptive version of the boost by majority algorithm and combines bounded goals of the boost by majority algorith...
Yoav Freund
COLT
2001
Springer
14 years 4 months ago
Smooth Boosting and Learning with Malicious Noise
We describe a new boosting algorithm which generates only smooth distributions which do not assign too much weight to any single example. We show that this new boosting algorithm ...
Rocco A. Servedio
ECML
2007
Springer
14 years 5 months ago
Scale-Space Based Weak Regressors for Boosting
Boosting is a simple yet powerful modeling technique that is used in many machine learning and data mining related applications. In this paper, we propose a novel scale-space based...
Jin Hyeong Park, Chandan K. Reddy
CIKM
2009
Springer
14 years 6 months ago
A general magnitude-preserving boosting algorithm for search ranking
Traditional boosting algorithms for the ranking problems usually employ the pairwise approach and convert the document rating preference into a binary-value label, like RankBoost....
Chenguang Zhu, Weizhu Chen, Zeyuan Allen Zhu, Gang...
ICML
2005
IEEE
15 years 10 days ago
A smoothed boosting algorithm using probabilistic output codes
AdaBoost.OC has shown to be an effective method in boosting "weak" binary classifiers for multi-class learning. It employs the Error Correcting Output Code (ECOC) method...
Rong Jin, Jian Zhang