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COLT
2008
Springer
13 years 9 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
13 years 6 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...
ICML
1999
IEEE
14 years 8 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»
11 years 10 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...
SBACPAD
2007
IEEE
129views Hardware» more  SBACPAD 2007»
14 years 1 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