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ISMB
2000
15 years 6 months ago
A Probabilistic Learning Approach to Whole-Genome Operon Prediction
We present a computational approach to predicting operons in the genomes of prokaryotic organisms. Our approach uses machine learning methods to induce predictive models for this ...
Mark Craven, David Page, Jude W. Shavlik, Joseph B...
SIGMOD
2008
ACM
162views Database» more  SIGMOD 2008»
16 years 4 months ago
Event queries on correlated probabilistic streams
A major problem in detecting events in streams of data is that the data can be imprecise (e.g. RFID data). However, current state-ofthe-art event detection systems such as Cayuga ...
Christopher Ré, Dan Suciu, Julie Letchner, ...
FOSSACS
2005
Springer
15 years 10 months ago
Branching Cells as Local States for Event Structures and Nets: Probabilistic Applications
We study the concept of choice for true concurrency models such as prime event structures and safe Petri nets. We propose a dynamic variation of the notion of cluster previously in...
Samy Abbes, Albert Benveniste
151
Voted
KR
2004
Springer
15 years 10 months ago
Learning Probabilistic Relational Planning Rules
To learn to behave in highly complex domains, agents must represent and learn compact models of the world dynamics. In this paper, we present an algorithm for learning probabilist...
Hanna Pasula, Luke S. Zettlemoyer, Leslie Pack Kae...
CIKM
2009
Springer
15 years 9 months ago
Probabilistic skyline queries
The ability to deal with uncertain information is becoming increasingly important for modern database applications. Whereas a conventional (certain) object is usually represented ...
Christian Böhm, Frank Fiedler, Annahita Oswal...