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» Large-scale manifold learning
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ICCV
2011
IEEE
12 years 10 months ago
Strong Supervision From Weak Annotation: Interactive Training of Deformable Part Models
We propose a framework for large scale learning and annotation of structured models. The system interleaves interactive labeling (where the current model is used to semiautomate t...
Steven Branson, Pietro Perona, Serge Belongie
BMCBI
2007
126views more  BMCBI 2007»
13 years 10 months ago
High-throughput identification of interacting protein-protein binding sites
Background: With the advent of increasing sequence and structural data, a number of methods have been proposed to locate putative protein binding sites from protein surfaces. Ther...
Jo-Lan Chung, Wei Wang, Philip E. Bourne
MM
2004
ACM
152views Multimedia» more  MM 2004»
14 years 3 months ago
Manifold-ranking based image retrieval
In this paper, we propose a novel transductive learning framework named manifold-ranking based image retrieval (MRBIR). Given a query image, MRBIR first makes use of a manifold ra...
Jingrui He, Mingjing Li, HongJiang Zhang, Hanghang...
NIPS
2008
13 years 11 months ago
Regularized Learning with Networks of Features
For many supervised learning problems, we possess prior knowledge about which features yield similar information about the target variable. In predicting the topic of a document, ...
Ted Sandler, John Blitzer, Partha Pratim Talukdar,...
PAMI
2011
13 years 4 months ago
Semi-Supervised Learning via Regularized Boosting Working on Multiple Semi-Supervised Assumptions
—Semi-supervised learning concerns the problem of learning in the presence of labeled and unlabeled data. Several boosting algorithms have been extended to semi-supervised learni...
Ke Chen, Shihai Wang