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» Maximum likelihood analysis of algorithms and data structure...
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IJCAI
1997
13 years 9 months ago
On the Role of Hierarchy for Neural Network Interpretation
In this paper, we concentrate on the expressive power of hierarchical structures in neural networks. Recently, the so-called SplitNet model was introduced. It develops a dynamic n...
Jürgen Rahmel, Christian Blum, Peter Hahn
PKDD
1999
Springer
130views Data Mining» more  PKDD 1999»
14 years 9 days ago
OPTICS-OF: Identifying Local Outliers
: For many KDD applications finding the outliers, i.e. the rare events, is more interesting and useful than finding the common cases, e.g. detecting criminal activities in E-commer...
Markus M. Breunig, Hans-Peter Kriegel, Raymond T. ...
WADS
2009
Springer
232views Algorithms» more  WADS 2009»
14 years 2 months ago
On Making Directed Graphs Transitive
We present the first thorough theoretical analysis of the Transitivity Editing problem on digraphs. Herein, the task is to perform a minimum number of arc insertions or deletions ...
Mathias Weller, Christian Komusiewicz, Rolf Nieder...
ICALP
2009
Springer
14 years 8 months ago
Counting Subgraphs via Homomorphisms
We introduce a generic approach for counting subgraphs in a graph. The main idea is to relate counting subgraphs to counting graph homomorphisms. This approach provides new algori...
Omid Amini, Fedor V. Fomin, Saket Saurabh
SODA
2008
ACM
110views Algorithms» more  SODA 2008»
13 years 9 months ago
Why simple hash functions work: exploiting the entropy in a data stream
Hashing is fundamental to many algorithms and data structures widely used in practice. For theoretical analysis of hashing, there have been two main approaches. First, one can ass...
Michael Mitzenmacher, Salil P. Vadhan