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SIGIR
2008
ACM
13 years 8 months ago
Learning to rank with partially-labeled data
Ranking algorithms, whose goal is to appropriately order a set of objects/documents, are an important component of information retrieval systems. Previous work on ranking algorith...
Kevin Duh, Katrin Kirchhoff
TIP
2010
155views more  TIP 2010»
13 years 7 months ago
Laplacian Regularized D-Optimal Design for Active Learning and Its Application to Image Retrieval
—In increasingly many cases of interest in computer vision and pattern recognition, one is often confronted with the situation where data size is very large. Usually, the labels ...
Xiaofei He
ICMCS
2007
IEEE
146views Multimedia» more  ICMCS 2007»
14 years 3 months ago
A Max Margin Framework on Image Annotation and Multimodal Image Retrieval
This paper presents a max margin framework on image annotation and multimodal image retrieval as a structured prediction model. Following the max margin approach the image retriev...
Zhen Guo, Zhongfei Zhang, Eric P. Xing, Christos F...
CVPR
2010
IEEE
14 years 2 months ago
Image Retrieval via Probabilistic Hypergraph Ranking
In this paper, we propose a new transductive learning framework for image retrieval, in which images are taken as vertices in a weighted hypergraph and the task of image search is...
Yuchi Huang, Qingshan Liu, Shaoting Zhang, Metaxas...
ICPR
2000
IEEE
14 years 10 months ago
Feature Relevance Learning with Query Shifting for Content-Based Image Retrieval
Probabilistic feature relevance learning (PFRL) is an effective technique for adaptively computing local feature relevance for content-based image retrieval. It however becomes le...
Douglas R. Heisterkamp, Jing Peng, H. K. Dai