Sciweavers

50 search results - page 1 / 10
» Learning Complex and Sparse Events in Long Sequences
Sort
View
ECAI
2004
Springer
14 years 27 days ago
Learning Complex and Sparse Events in Long Sequences
The Hierarchical Hidden Markov Model (HHMM) is a well formalized tool suitable to model complex patterns in long temporal or spatial sequences. Even if effective algorithms are ava...
Marco Botta, Ugo Galassi, Attilio Giordana
SARA
2005
Springer
14 years 29 days ago
Learning Regular Expressions from Noisy Sequences
Abstract. The presence of long gaps dramatically increases the difficulty of detecting and characterizing complex events hidden in long sequences. In order to cope with this proble...
Ugo Galassi, Attilio Giordana
HCI
2009
13 years 5 months ago
Studying Reactive, Risky, Complex, Long-Spanning, and Collaborative Work: The Case of IT Service Delivery
Abstract. IT service delivery is challenging to study. It is characterized by interacting systems of technology, people, and organizations. The work is sometimes reactive, sometime...
Eser Kandogan, Eben M. Haber, John H. Bailey, Paul...
JAIR
2002
134views more  JAIR 2002»
13 years 7 months ago
Specific-to-General Learning for Temporal Events with Application to Learning Event Definitions from Video
We develop, analyze, and evaluate a novel, supervised, specific-to-general learner for a simple temporal logic and use the resulting algorithm to learn visual event definitions fr...
Alan Fern, Robert Givan, Jeffrey Mark Siskind
BMCBI
2007
147views more  BMCBI 2007»
13 years 7 months ago
Comparative analysis of long DNA sequences by per element information content using different contexts
Background: Features of a DNA sequence can be found by compressing the sequence under a suitable model; good compression implies low information content. Good DNA compression mode...
Trevor I. Dix, David R. Powell, Lloyd Allison, Jul...