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» Boosting Methods for Regression
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KDD
2008
ACM
135views Data Mining» more  KDD 2008»
14 years 10 months ago
Effective and efficient itemset pattern summarization: regression-based approaches
In this paper, we propose a set of novel regression-based approaches to effectively and efficiently summarize frequent itemset patterns. Specifically, we show that the problem of ...
Ruoming Jin, Muad Abu-Ata, Yang Xiang, Ning Ruan
CVPR
2010
IEEE
14 years 6 months ago
Locally-Parametric Pictorial Structures
Pictorial structure (PS) models are extensively used for part-based recognition of scenes, people, animals and multi-part objects. To achieve tractability, the structure and param...
Benjamin Sapp, Chris Jordan, Ben Taskar
CVPR
2012
IEEE
12 years 16 days ago
Cross-based local multipoint filtering
This paper presents a cross-based framework of performing local multipoint filtering efficiently. We formulate the filtering process as a local multipoint regression problem, c...
Jiangbo Lu, Keyang Shi, Dongbo Min, Liang Lin, Min...
JCISD
2006
114views more  JCISD 2006»
13 years 10 months ago
Ensemble of Linear Models for Predicting Drug Properties
We propose a new classification method for prediction of drug properties, called the Random Feature Subset Boosting for Linear Discriminant Analysis (LDA). The main novelty of this...
Tomasz Arodz, David A. Yuen, Arkadiusz Z. Dudek
DFT
2008
IEEE
82views VLSI» more  DFT 2008»
14 years 4 months ago
Selective Hardening of NanoPLA Circuits
Nanoelectronic components are expected to suffer from very high error rates, implying the need for hardening techniques. We propose a fine-grained approach to harden a promising...
Ilia Polian, Wenjing Rao