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» Learning with Constrained and Unlabelled Data
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SIGIR
2008
ACM
13 years 9 months ago
Topic-bridged PLSA for cross-domain text classification
In many Web applications, such as blog classification and newsgroup classification, labeled data are in short supply. It often happens that obtaining labeled data in a new domain ...
Gui-Rong Xue, Wenyuan Dai, Qiang Yang, Yong Yu
PKDD
2010
Springer
188views Data Mining» more  PKDD 2010»
13 years 8 months ago
Semi-supervised Abstraction-Augmented String Kernel for Multi-level Bio-Relation Extraction
ervised Abstraction-Augmented String Kernel for Multi-Level Bio-Relation Extraction Pavel Kuksa1 , Yanjun Qi2 , Bing Bai2 , Ronan Collobert2 , Jason Weston3 , Vladimir Pavlovic1 , ...
Pavel P. Kuksa, Yanjun Qi, Bing Bai, Ronan Collobe...
HICSS
2003
IEEE
118views Biometrics» more  HICSS 2003»
14 years 3 months ago
Lessons Learned from Real DSL Experiments
Over the years, our group, led by Bob Balzer, designed and implemented three domain-specific languages for use by outside people in real situations. The first language described t...
David S. Wile
ICDM
2007
IEEE
96views Data Mining» more  ICDM 2007»
14 years 4 months ago
The Chosen Few: On Identifying Valuable Patterns
Constrained pattern mining extracts patterns based on their individual merit. Usually this results in far more patterns than a human expert or a machine learning technique could m...
Björn Bringmann, Albrecht Zimmermann
ICCV
2009
IEEE
1556views Computer Vision» more  ICCV 2009»
15 years 2 months ago
Kernel Methods for Weakly Supervised Mean Shift Clustering
Mean shift clustering is a powerful unsupervised data analysis technique which does not require prior knowledge of the number of clusters, and does not constrain the shape of th...
Oncel Tuzel, Fatih Porikli, Peter Meer