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ICML
2005
IEEE
16 years 5 months ago
Learning first-order probabilistic models with combining rules
Many real-world domains exhibit rich relational structure and stochasticity and motivate the development of models that combine predicate logic with probabilities. These models de...
Sriraam Natarajan, Prasad Tadepalli, Eric Altendor...
KDD
2006
ACM
240views Data Mining» more  KDD 2006»
16 years 5 months ago
Adaptive event detection with time-varying poisson processes
Time-series of count data are generated in many different contexts, such as web access logging, freeway traffic monitoring, and security logs associated with buildings. Since this...
Alexander T. Ihler, Jon Hutchins, Padhraic Smyth
KDD
2006
ACM
115views Data Mining» more  KDD 2006»
16 years 5 months ago
Supervised probabilistic principal component analysis
Principal component analysis (PCA) has been extensively applied in data mining, pattern recognition and information retrieval for unsupervised dimensionality reduction. When label...
Shipeng Yu, Kai Yu, Volker Tresp, Hans-Peter Krieg...
MLDM
2005
Springer
15 years 10 months ago
Supervised Evaluation of Dataset Partitions: Advantages and Practice
In the context of large databases, data preparation takes a greater importance : instances and explanatory attributes have to be carefully selected. In supervised learning, instanc...
Sylvain Ferrandiz, Marc Boullé
SIGIR
2010
ACM
15 years 9 months ago
Self-taught hashing for fast similarity search
The ability of fast similarity search at large scale is of great importance to many Information Retrieval (IR) applications. A promising way to accelerate similarity search is sem...
Dell Zhang, Jun Wang, Deng Cai, Jinsong Lu