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KDD
2004
ACM
160views Data Mining» more  KDD 2004»
15 years 10 months ago
Boosting for Text Classification with Semantic Features
Abstract. Current text classification systems typically use term stems for representing document content. Semantic Web technologies allow the usage of features on a higher semantic...
Stephan Bloehdorn, Andreas Hotho
GFKL
2007
Springer
164views Data Mining» more  GFKL 2007»
15 years 1 months ago
Classification with Invariant Distance Substitution Kernels
Kernel methods offer a flexible toolbox for pattern analysis and machine learning. A general class of kernel functions which incorporates known pattern invariances are invariant d...
Bernard Haasdonk, Hans Burkhardt
UAI
1996
14 years 11 months ago
Bayesian Learning of Loglinear Models for Neural Connectivity
This paper presents a Bayesian approach to learning the connectivity structure of a group of neurons from data on configuration frequencies. A major objective of the research is t...
Kathryn B. Laskey, Laura Martignon
ICML
2010
IEEE
14 years 10 months ago
Deep Supervised t-Distributed Embedding
Deep learning has been successfully applied to perform non-linear embedding. In this paper, we present supervised embedding techniques that use a deep network to collapse classes....
Martin Renqiang Min, Laurens van der Maaten, Zinen...
ICDM
2006
IEEE
89views Data Mining» more  ICDM 2006»
15 years 3 months ago
On the Lower Bound of Local Optimums in K-Means Algorithm
The k-means algorithm is a popular clustering method used in many different fields of computer science, such as data mining, machine learning and information retrieval. However, ...
Zhenjie Zhang, Bing Tian Dai, Anthony K. H. Tung