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» Learning to rank with multiple objective functions
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JIFS
2002
107views more  JIFS 2002»
14 years 11 months ago
Model selection via Genetic Algorithms for RBF networks
This work addresses the problem of finding the adjustable parameters of a learning algorithm using Genetic Algorithms. This problem is also known as the model selection problem. In...
Estefane G. M. de Lacerda, André Carlos Pon...
140
Voted
CVPR
2011
IEEE
14 years 3 months ago
Effective 3D Object Detection and Regression Using Probabilistic Segmentation Features in CT Images
3D object detection and importance regression/ranking are at the core for semantically interpreting 3D medical images of computer aided diagnosis (CAD). In this paper, we propose ...
Le Lu, Jinbo Bi, Matthias Wolf, Marcos Salganicoff
AAAI
2012
13 years 2 months ago
Relative Attributes for Enhanced Human-Machine Communication
We propose to model relative attributes1 that capture the relationships between images and objects in terms of human-nameable visual properties. For example, the models can captur...
Devi Parikh, Adriana Kovashka, Amar Parkash, Krist...
87
Voted
ICML
2009
IEEE
16 years 14 days ago
A Bayesian approach to protein model quality assessment
Given multiple possible models b1, b2, . . . bn for a protein structure, a common sub-task in in-silico Protein Structure Prediction is ranking these models according to their qua...
Hetunandan Kamisetty, Christopher James Langmead
WWW
2007
ACM
16 years 10 days ago
Web object retrieval
The primary function of current Web search engines is essentially relevance ranking at the document level. However, myriad structured information about real-world objects is embed...
Zaiqing Nie, Yunxiao Ma, Shuming Shi, Ji-Rong Wen,...