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» Theoretical Frameworks for Data Mining
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CIKM
2010
Springer
13 years 7 months ago
Combining link and content for collective active learning
In this paper, we study a novel problem Collective Active Learning, in which we aim to select a batch set of "informative" instances from a networking data set to query ...
Lixin Shi, Yuhang Zhao, Jie Tang
PAMI
2006
208views more  PAMI 2006»
13 years 9 months ago
Combining Reconstructive and Discriminative Subspace Methods for Robust Classification and Regression by Subsampling
Linear subspace methods that provide sufficient reconstruction of the data, such as PCA, offer an efficient way of dealing with missing pixels, outliers, and occlusions that often ...
Sanja Fidler, Danijel Skocaj, Ales Leonardis
SDM
2009
SIAM
118views Data Mining» more  SDM 2009»
14 years 6 months ago
Finding Links and Initiators: A Graph-Reconstruction Problem.
Consider a 0–1 observation matrix M, where rows correspond to entities and columns correspond to signals; a value of 1 (or 0) in cell (i, j) of M indicates that signal j has bee...
Evimaria Terzi, Heikki Mannila
SSDBM
2010
IEEE
188views Database» more  SSDBM 2010»
14 years 2 months ago
Similarity Estimation Using Bayes Ensembles
Similarity search and data mining often rely on distance or similarity functions in order to provide meaningful results and semantically meaningful patterns. However, standard dist...
Tobias Emrich, Franz Graf, Hans-Peter Kriegel, Mat...
CRYPTO
2004
Springer
86views Cryptology» more  CRYPTO 2004»
14 years 2 months ago
On Multiple Linear Approximations
In this paper we study the long standing problem of information extraction from multiple linear approximations. We develop a formal statistical framework for block cipher attacks b...
Alex Biryukov, Christophe De Cannière, Mich...