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» Semi-supervised Learning from General Unlabeled Data
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WWW
2011
ACM
13 years 3 months ago
Learning to rank with multiple objective functions
We investigate the problem of learning to rank for document retrieval from the perspective of learning with multiple objective functions. We present solutions to two open problems...
Krysta Marie Svore, Maksims Volkovs, Christopher J...
SIGIR
2012
ACM
11 years 10 months ago
Top-k learning to rank: labeling, ranking and evaluation
In this paper, we propose a novel top-k learning to rank framework, which involves labeling strategy, ranking model and evaluation measure. The motivation comes from the difficul...
Shuzi Niu, Jiafeng Guo, Yanyan Lan, Xueqi Cheng
KDD
2007
ACM
132views Data Mining» more  KDD 2007»
14 years 8 months ago
LungCAD: a clinically approved, machine learning system for lung cancer detection
We present LungCAD, a computer aided diagnosis (CAD) system that employs a classification algorithm for detecting solid pulmonary nodules from CT thorax studies. We briefly descri...
R. Bharat Rao, Jinbo Bi, Glenn Fung, Marcos Salgan...
FTCGV
2011
122views more  FTCGV 2011»
12 years 11 months ago
Structured Learning and Prediction in Computer Vision
Powerful statistical models that can be learned efficiently from large amounts of data are currently revolutionizing computer vision. These models possess a rich internal structur...
Sebastian Nowozin, Christoph H. Lampert
WWW
2004
ACM
14 years 8 months ago
Dynamic assembly of learning objects
This paper describes one solution to the problem of how to select sequence, and link Web resources into a coherent, focused organization for instruction that addresses a user'...
Robert G. Farrell, Soyini D. Liburd, John C. Thoma...