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COLT
2008
Springer
15 years 2 months ago
On the Equivalence of Weak Learnability and Linear Separability: New Relaxations and Efficient Boosting Algorithms
Boosting algorithms build highly accurate prediction mechanisms from a collection of lowaccuracy predictors. To do so, they employ the notion of weak-learnability. The starting po...
Shai Shalev-Shwartz, Yoram Singer
IR
2010
14 years 11 months ago
Adapting boosting for information retrieval measures
Abstract We present a new ranking algorithm that combines the strengths of two previous methods: boosted tree classification, and LambdaRank, which has been shown to be empiricall...
Qiang Wu, Christopher J. C. Burges, Krysta Marie S...
105
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ICML
1999
IEEE
16 years 1 months ago
The Alternating Decision Tree Learning Algorithm
The applicationofboosting procedures to decision tree algorithmshas been shown to produce very accurate classi ers. These classiers are in the form of a majority vote over a numbe...
Yoav Freund, Llew Mason
SDM
2012
SIAM
252views Data Mining» more  SDM 2012»
13 years 3 months ago
Learning from Heterogeneous Sources via Gradient Boosting Consensus
Multiple data sources containing different types of features may be available for a given task. For instance, users’ profiles can be used to build recommendation systems. In a...
Xiaoxiao Shi, Jean-François Paiement, David...
122
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SBACPAD
2007
IEEE
129views Hardware» more  SBACPAD 2007»
15 years 7 months ago
Predicting Loop Termination to Boost Speculative Thread-Level Parallelism in Embedded Applications
The necessity of devising novel thread-level speculation (TLS) techniques has become extremely important with the growing acceptance of multi-core architectures by the industry. H...
Md. Mafijul Islam