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KDD
2004
ACM
141views Data Mining» more  KDD 2004»
16 years 3 months ago
A Maximum Entropy Approach to Biomedical Named Entity Recognition
Machine learning approaches are frequently used to solve name entity (NE) recognition (NER). In this paper we propose a hybrid method that uses maximum entropy (ME) as the underly...
Yi-Feng Lin, Tzong-Han Tsai, Wen-Chi Chou, Kuen-Pi...
ICML
2008
IEEE
16 years 4 months ago
Optimizing estimated loss reduction for active sampling in rank learning
Learning to rank is becoming an increasingly popular research area in machine learning. The ranking problem aims to induce an ordering or preference relations among a set of insta...
Pinar Donmez, Jaime G. Carbonell
KDD
2004
ACM
132views Data Mining» more  KDD 2004»
16 years 3 months ago
Privacy preserving regression modelling via distributed computation
Reluctance of data owners to share their possibly confidential or proprietary data with others who own related databases is a serious impediment to conducting a mutually beneficia...
Ashish P. Sanil, Alan F. Karr, Xiaodong Lin, Jerom...
KDD
2004
ACM
113views Data Mining» more  KDD 2004»
16 years 3 months ago
Learning spatially variant dissimilarity (SVaD) measures
Clustering algorithms typically operate on a feature vector representation of the data and find clusters that are compact with respect to an assumed (dis)similarity measure betwee...
Krishna Kummamuru, Raghu Krishnapuram, Rakesh Agra...
ICML
2008
IEEE
16 years 4 months ago
The asymptotics of semi-supervised learning in discriminative probabilistic models
Semi-supervised learning aims at taking advantage of unlabeled data to improve the efficiency of supervised learning procedures. For discriminative models however, this is a chall...
François Yvon, Nataliya Sokolovska, Olivier...