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» The Tradeoffs of Large Scale Learning
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ICMLA
2004
13 years 9 months ago
Two new regularized AdaBoost algorithms
AdaBoost rarely suffers from overfitting problems in low noise data cases. However, recent studies with highly noisy patterns clearly showed that overfitting can occur. A natural s...
Yijun Sun, Jian Li, William W. Hager
SDM
2003
SIAM
129views Data Mining» more  SDM 2003»
13 years 9 months ago
Approximate Query Answering by Model Averaging
In earlier work we have introduced and explored a variety of different probabilistic models for the problem of answering selectivity queries posed to large sparse binary data set...
Dmitry Pavlov, Padhraic Smyth
CLEF
2010
Springer
13 years 9 months ago
Detection of Visual Concepts and Annotation of Images Using Predictive Clustering Trees
Abstract. In this paper, we present a multiple targets classification system for visual concepts detection and image annotation. Multiple targets classification (MTC) is a variant ...
Ivica Dimitrovski, Dragi Kocev, Suzana Loskovska, ...
JMLR
2008
209views more  JMLR 2008»
13 years 7 months ago
Bayesian Inference and Optimal Design for the Sparse Linear Model
The linear model with sparsity-favouring prior on the coefficients has important applications in many different domains. In machine learning, most methods to date search for maxim...
Matthias W. Seeger
FCSC
2007
159views more  FCSC 2007»
13 years 7 months ago
Ranking with uncertain labels and its applications
1 The techniques for image analysis and classi cation generally consider the image sample labels xed and without uncertainties. The rank regression problem is studied in this pape...
Shuicheng Yan, Huan Wang, Jianzhuang Liu, Xiaoou T...