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SCHOLARPEDIA
2008
89views more  SCHOLARPEDIA 2008»
15 years 3 months ago
Support vector clustering
We present a novel method for clustering using the support vector machine approach. Data points are mapped to a high dimensional feature space, where support vectors are used to d...
Asa Ben-Hur
NIPS
1998
15 years 6 months ago
Approximate Learning of Dynamic Models
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
Xavier Boyen, Daphne Koller
KDD
2012
ACM
212views Data Mining» more  KDD 2012»
13 years 7 months ago
Fast bregman divergence NMF using taylor expansion and coordinate descent
Non-negative matrix factorization (NMF) provides a lower rank approximation of a matrix. Due to nonnegativity imposed on the factors, it gives a latent structure that is often mor...
Liangda Li, Guy Lebanon, Haesun Park
KDD
2004
ACM
127views Data Mining» more  KDD 2004»
16 years 5 months ago
A generative probabilistic approach to visualizing sets of symbolic sequences
There is a notable interest in extending probabilistic generative modeling principles to accommodate for more complex structured data types. In this paper we develop a generative ...
Peter Tiño, Ata Kabán, Yi Sun
IEEESCC
2008
IEEE
15 years 11 months ago
Exploiting XML Schema for Interpreting XML Documents as RDF
Interpreting legacy XML documents is a great challenge for realizing the vision of the Semantic Web (SW). This paper presents an algorithm to transform XML data into RDF- foundati...
Pham Thi Thu Thuy, Young-Koo Lee, Sungyoung Lee, B...