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» An algorithmic framework for network reconstruction
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ILP
1999
Springer
13 years 12 months ago
Probabilistic Relational Models
Most real-world data is heterogeneous and richly interconnected. Examples include the Web, hypertext, bibliometric data and social networks. In contrast, most statistical learning...
Daphne Koller
DAGM
2008
Springer
13 years 9 months ago
Natural Language Understanding by Combining Statistical Methods and Extended Context-Free Grammars
This paper introduces an novel framework for speech understanding using extended context-free grammars (ECFGs) by combining statistical methods and rule based knowledge. By only us...
Stefan Schwärzler, Joachim Schenk, Frank Wall...
DMS
2008
106views Multimedia» more  DMS 2008»
13 years 9 months ago
A Multimedia Data Streams Model for Content-based Information Retrieval
: Multimedia applications nowadays are becoming the standard, for they utilize the enormous human brain computational power. In the past, the Relational Database Model was generali...
Shenoda Guirguis, Rohit Kulkarni, Shi-Kuo Chang
PETRA
2010
ACM
13 years 7 months ago
Optimizing pervasive sensor data acquisition utilizing missing values substitution
Acquisition of pervasive sensor data can be often unsuccessful due to power outage at nodes, time synchronization issues, interference, network transmission failures or sensor har...
M. Michalopoulos, Christos Anagnostopoulos, Charal...
JMLR
2008
148views more  JMLR 2008»
13 years 7 months ago
Linear-Time Computation of Similarity Measures for Sequential Data
Efficient and expressive comparison of sequences is an essential procedure for learning with sequential data. In this article we propose a generic framework for computation of sim...
Konrad Rieck, Pavel Laskov