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ICML
2010
IEEE
15 years 7 months ago
Hilbert Space Embeddings of Hidden Markov Models
Hidden Markov Models (HMMs) are important tools for modeling sequence data. However, they are restricted to discrete latent states, and are largely restricted to Gaussian and disc...
Le Song, Sajid M. Siddiqi, Geoffrey J. Gordon, Ale...
191
Voted
DEBU
2010
238views more  DEBU 2010»
15 years 6 months ago
Spatio-Temporal Access Methods: Part 2 (2003 - 2010)
In spatio-temporal applications, moving objects detect their locations via location-aware devices and update their locations continuously to the server. With the ubiquity and mass...
Long-Van Nguyen-Dinh, Walid G. Aref, Mohamed F. Mo...
ICDM
2007
IEEE
132views Data Mining» more  ICDM 2007»
16 years 29 days ago
Learning What Makes a Society Tick
We present a machine learning methodology (models, algorithms, and experimental data) to discovering the agent dynamics that drive the evolution of the social groups in a communit...
Hung-Ching Chen, Mark K. Goldberg, Malik Magdon-Is...
BTW
2007
Springer
152views Database» more  BTW 2007»
16 years 25 days ago
Armada: a Reference Model for an Evolving Database System
Abstract: The data on the web, in digital libraries, in scientific repositories, etc. continues to grow at an increasing rate. Distribution is a key solution to overcome this data...
Fabian Groffen, Martin L. Kersten, Stefan Manegold
CIKM
2007
Springer
16 years 25 days ago
Modeling historical and future movements of spatio-temporal objects in moving objects databases
Spatio-temporal databases deal with geometries changing over time. In general, geometries do not only change discretely but continuously; hence we are dealing with moving objects....
Reasey Praing, Markus Schneider