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NIPS
2001
13 years 9 months ago
Natural Language Grammar Induction Using a Constituent-Context Model
This paper presents a novel approach to the unsupervised learning of syntactic analyses of natural language text. Most previous work has focused on maximizing likelihood according...
Dan Klein, Christopher D. Manning
DATAMINE
2010
161views more  DATAMINE 2010»
13 years 5 months ago
Predicting labels for dyadic data
: In dyadic prediction, the input consists of a pair of items (a dyad), and the goal is to predict the value of an observation related to the dyad. Special cases of dyadic predicti...
Aditya Krishna Menon, Charles Elkan
KDD
2007
ACM
276views Data Mining» more  KDD 2007»
14 years 8 months ago
Nonlinear adaptive distance metric learning for clustering
A good distance metric is crucial for many data mining tasks. To learn a metric in the unsupervised setting, most metric learning algorithms project observed data to a lowdimensio...
Jianhui Chen, Zheng Zhao, Jieping Ye, Huan Liu
ICML
2008
IEEE
14 years 8 months ago
The skew spectrum of graphs
The central issue in representing graphstructured data instances in learning algorithms is designing features which are invariant to permuting the numbering of the vertices. We pr...
Risi Imre Kondor, Karsten M. Borgwardt
SDM
2007
SIAM
184views Data Mining» more  SDM 2007»
13 years 9 months ago
Mining Naturally Smooth Evolution of Clusters from Dynamic Data
Many clustering algorithms have been proposed to partition a set of static data points into groups. In this paper, we consider an evolutionary clustering problem where the input d...
Yi Wang, Shi-Xia Liu, Jianhua Feng, Lizhu Zhou