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» Learning with Constrained and Unlabelled Data
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SIGIR
2008
ACM
15 years 5 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»
15 years 4 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»
15 years 11 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»
16 years 4 days 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»
16 years 10 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