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SIGIR
2011
ACM
14 years 9 months ago
A boosting approach to improving pseudo-relevance feedback
Pseudo-relevance feedback has proven effective for improving the average retrieval performance. Unfortunately, many experiments have shown that although pseudo-relevance feedback...
Yuanhua Lv, ChengXiang Zhai, Wan Chen
EMMCVPR
2011
Springer
14 years 6 months ago
Optimization of Robust Loss Functions for Weakly-Labeled Image Taxonomies: An ImageNet Case Study
The recently proposed ImageNet dataset consists of several million images, each annotated with a single object category. However, these annotations may be imperfect, in the sense t...
Julian John McAuley, Arnau Ramisa, Tibério ...
DAGM
2011
Springer
14 years 6 months ago
Agnostic Domain Adaptation
The supervised learning paradigm assumes in general that both training and test data are sampled from the same distribution. When this assumption is violated, we are in the setting...
Alexander Vezhnevets, Joachim M. Buhmann
KDD
2012
ACM
247views Data Mining» more  KDD 2012»
13 years 9 months ago
Integrating meta-path selection with user-guided object clustering in heterogeneous information networks
Real-world, multiple-typed objects are often interconnected, forming heterogeneous information networks. A major challenge for link-based clustering in such networks is its potent...
Yizhou Sun, Brandon Norick, Jiawei Han, Xifeng Yan...
SDM
2012
SIAM
216views Data Mining» more  SDM 2012»
13 years 9 months ago
Feature Selection "Tomography" - Illustrating that Optimal Feature Filtering is Hopelessly Ungeneralizable
:  Feature Selection “Tomography” - Illustrating that Optimal Feature Filtering is Hopelessly Ungeneralizable George Forman HP Laboratories HPL-2010-19R1 Feature selection; ...
George Forman
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