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118
Voted
KDD
2008
ACM
147views Data Mining» more  KDD 2008»
16 years 1 months ago
Structured learning for non-smooth ranking losses
Learning to rank from relevance judgment is an active research area. Itemwise score regression, pairwise preference satisfaction, and listwise structured learning are the major te...
Soumen Chakrabarti, Rajiv Khanna, Uma Sawant, Chir...
120
Voted
KDD
2007
ACM
191views Data Mining» more  KDD 2007»
16 years 1 months ago
Cost-effective outbreak detection in networks
Given a water distribution network, where should we place sensors to quickly detect contaminants? Or, which blogs should we read to avoid missing important stories? These seemingl...
Andreas Krause, Carlos Guestrin, Christos Faloutso...
150
Voted
KDD
2012
ACM
205views Data Mining» more  KDD 2012»
13 years 3 months ago
Rank-loss support instance machines for MIML instance annotation
Multi-instance multi-label learning (MIML) is a framework for supervised classification where the objects to be classified are bags of instances associated with multiple labels....
Forrest Briggs, Xiaoli Z. Fern, Raviv Raich
134
Voted
EMNLP
2011
14 years 10 days ago
Watermarking the Outputs of Structured Prediction with an application in Statistical Machine Translation
We propose a general method to watermark and probabilistically identify the structured outputs of machine learning algorithms. Our method is robust to local editing operations and...
Ashish Venugopal, Jakob Uszkoreit, David Talbot, F...
CIKM
2008
Springer
15 years 2 months ago
Intra-document structural frequency features for semi-supervised domain adaptation
In this work we try to bridge the gap often encountered by researchers who find themselves with few or no labeled examples from their desired target domain, yet still have access ...
Andrew Arnold, William W. Cohen